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Roldán D, Redenbach C, Schladitz K, Kübel C, Schlabach S. Image quality evaluation for FIB-SEM images. J Microsc 2024; 293:98-117. [PMID: 38112173 DOI: 10.1111/jmi.13254] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2023] [Revised: 11/20/2023] [Accepted: 11/21/2023] [Indexed: 12/20/2023]
Abstract
Focused ion beam scanning electron microscopy (FIB-SEM) tomography is a serial sectioning technique where an FIB mills off slices from the material sample that is being analysed. After every slicing, an SEM image is taken showing the newly exposed layer of the sample. By combining all slices in a stack, a 3D image of the material is generated. However, specific artefacts caused by the imaging technique distort the images, hampering the morphological analysis of the structure. Typical quality problems in microscopy imaging are noise and lack of contrast or focus. Moreover, specific artefacts are caused by the FIB milling, namely, curtaining and charging artefacts. We propose quality indices for the evaluation of the quality of FIB-SEM data sets. The indices are validated on real and experimental data of different structures and materials.
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Affiliation(s)
| | | | - Katja Schladitz
- Fraunhofer Institute of Industrial Mathematics, Kaiserslautern, Germany
| | - Christian Kübel
- Institute of Nanotechnology (INT), Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
- Karlsruhe Nano Micro Facility (KNMFi), Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
- Research group in-situ electron microscopy, Joint Research Laboratory Nanomaterials, Department of Materials & Earth Sciences, Technical University Darmstadt, Darmstadt, Germany
| | - Sabine Schlabach
- Institute of Nanotechnology (INT), Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
- Karlsruhe Nano Micro Facility (KNMFi), Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
- Institute for Applied Materials (IAM), Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
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Kamarul Baharin MAS, Abdul Ghani AS, Mohammad-Noor N, Ismail HN, Syamsul Amri SQ. Automatic phytoplankton image smoothing through integrated dual image histogram specification and enhanced background removal method. THE IMAGING SCIENCE JOURNAL 2022. [DOI: 10.1080/13682199.2022.2149067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
| | - Ahmad Shahrizan Abdul Ghani
- Faculty of Manufacturing and Mechatronic Engineering Technology, Universiti Malaysia Pahang, Pekan, Malaysia
| | - Normawaty Mohammad-Noor
- Department of Marine Science, Kulliyyah of Science, Inter. Islamic University Malaysia, Kuantan, Malaysia
| | - Hasnun Nita Ismail
- Faculty of Applied Science, University Technology of MARA, Tapah Road, Malaysia
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Pandey AK, Sonker D, Chaudhary J, Jaleel J, Baghel V, Sharma PD, Patel C, Kumar R. Restoration of Tc-99m methyl diphosphonate bone scan image using Richardson-Lucy algorithm. Nucl Med Commun 2022; 43:518-528. [PMID: 35102077 DOI: 10.1097/mnm.0000000000001544] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
INTRODUCTION In this study, the optimal input parameters point spread function (PSF) and the number of iterations of the Richardson-Lucy algorithm were experimentally determined to restore Tc-99 m methyl diphosphonate (MDP) whole-body bone scan images. MATERIALS AND METHODS The experiment was performed on 60 anonymized Tc-99 m MDP whole-body bone scan images. Ten images were used for estimating the optimum value of PSF and the number of iterations to restore scintigraphic images. The remaining 50 images were used for validation of estimated parameters. The image quality of observed and restored images was assessed objectively using blind/referenceless image spatial quality evaluator (BRISQUE), mean brightness (MB), discrete entropy (DE), and edge-based contrast measure (EBCM) image quality metrics. Image quality was subjectively assessed by two nuclear medicine physicians (NMPs) by comparing the restored image quality with observed image quality and assigning a score to each image on the scale of 0-5. RESULTS Based on BRISQUE, MB, DE, and EBCM scores, the restored images were significantly sharper, less bright, had more detailed information, and had less contrast around edges compared to the input images. The restored images had improved resolution based on visual assessment as well; NMPs assigned an average image quality score of 4.00 to restored images. Maximum resolution enhancement was noticed at PSF (size: 11 pixels, sigma: 1.75 pixels) and the number of iterations = 10. With the increase in the number of iterations, noise also gets amplified along with resolution enhancement and affects the detectability of small lesions; in the case of relatively low noisy input images, the number of iterations = 5 gave better results. CONCLUSION Tc-99 m MDP bone scan images were restored to improve image quality using the Richardson-Lucy algorithm. The optimum value of the PSF parameter was found to be of size = 11 pixels and sigma = 1.75 pixels.
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Affiliation(s)
- Anil Kumar Pandey
- Department of Nuclear Medicine, All India Institute of Medical Sciences
| | - Damini Sonker
- Department of Nuclear Medicine, All India Institute of Medical Sciences
| | - Jagrati Chaudhary
- Department of Nuclear Medicine, All India Institute of Medical Sciences
| | - Jasim Jaleel
- Department of Nuclear Medicine, All India Institute of Medical Sciences
| | - Vivek Baghel
- Department of Nuclear Medicine, All India Institute of Medical Sciences
| | - Param D Sharma
- Department of Computer Science, SGTB Khalsa College, University of Delhi, New Delhi, India
| | - Chetan Patel
- Department of Nuclear Medicine, All India Institute of Medical Sciences
| | - Rakesh Kumar
- Department of Nuclear Medicine, All India Institute of Medical Sciences
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Agrawal S, Panda R, Mishro P, Abraham A. A novel joint histogram equalization based image contrast enhancement. JOURNAL OF KING SAUD UNIVERSITY - COMPUTER AND INFORMATION SCIENCES 2022. [DOI: 10.1016/j.jksuci.2019.05.010] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
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5
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Kumar R, Kumar Bhandari A. Luminosity and contrast enhancement of retinal vessel images using weighted average histogram. Biomed Signal Process Control 2022. [DOI: 10.1016/j.bspc.2021.103089] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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6
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Więcławek W, Danch-Wierzchowska M, Rudzki M, Sędziak-Marcinek B, Teper SJ. Ultra-Widefield Fluorescein Angiography Image Brightness Compensation Based on Geometrical Features. SENSORS (BASEL, SWITZERLAND) 2021; 22:12. [PMID: 35009554 PMCID: PMC8747562 DOI: 10.3390/s22010012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Revised: 12/08/2021] [Accepted: 12/16/2021] [Indexed: 06/14/2023]
Abstract
Ultra-widefield fluorescein angiography (UWFA) is an emerging imaging modality used to characterise pathologies in the retinal vasculature, such as microaneurysms (MAs) and vascular leakages. Despite its potential value for diagnosis and disease screening, objective quantitative assessment of retinal pathologies by UWFA is currently limited because laborious manual processing is required. In this report, we describe a geometrical method for uneven brightness compensation inherent to UWFA imaging technique. The correction function is based on the geometrical eyeball shape, therefore it is fully automated and depends only on pixel distance from the center of the imaged retina. The method's performance was assessed on a database containing 256 UWFA images with the use of several image quality measures that show the correction method improves image quality. The method is also compared to the commonly used CLAHE approach and was also employed in a pilot study for vascular segmentation, giving a noticeable improvement in segmentation results. Therefore, the method can be used as an image preprocessing step in retinal UWFA image analysis.
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Affiliation(s)
- Wojciech Więcławek
- Faculty of Biomedical Engineering, Silesian University of Technology, Roosevelta St. 40, 41-800 Zabrze, Poland; (M.D.-W.); (M.R.)
| | - Marta Danch-Wierzchowska
- Faculty of Biomedical Engineering, Silesian University of Technology, Roosevelta St. 40, 41-800 Zabrze, Poland; (M.D.-W.); (M.R.)
| | - Marcin Rudzki
- Faculty of Biomedical Engineering, Silesian University of Technology, Roosevelta St. 40, 41-800 Zabrze, Poland; (M.D.-W.); (M.R.)
| | - Bogumiła Sędziak-Marcinek
- Clinical Department of Ophthalmology, Faculty of Medical Sciences in Zabrze, Medical University of Silesia, Panewnicka St. 65, 40-760 Katowice, Poland; (B.S.-M.); (S.J.T.)
| | - Slawomir Jan Teper
- Clinical Department of Ophthalmology, Faculty of Medical Sciences in Zabrze, Medical University of Silesia, Panewnicka St. 65, 40-760 Katowice, Poland; (B.S.-M.); (S.J.T.)
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Mishro PK, Agrawal S, Panda R, Abraham A. A novel brightness preserving joint histogram equalization technique for contrast enhancement of brain MR images. Biocybern Biomed Eng 2021. [DOI: 10.1016/j.bbe.2021.04.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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Lecca M, Rizzi A, Serapioni RP. An Image Contrast Measure Based on Retinex Principles. IEEE TRANSACTIONS ON IMAGE PROCESSING : A PUBLICATION OF THE IEEE SIGNAL PROCESSING SOCIETY 2021; 30:3543-3554. [PMID: 33667163 DOI: 10.1109/tip.2021.3062724] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
The image contrast is a feature capturing the variation of the image signal across the space. Such a feature is very useful to describe the local image structure at different scales and thus it is relevant to many computer vision applications, like image/texture retrieval and object recognition. In this work, we present MiRCo, a novel measure of image contrast derived from the Retinex theory. MiRCo is robust against in-plane rotations and light changes at multiple scales. Thanks to these properties, MiRCo enables an accurate and robust description of the local image structure. Here we describe and discuss the mathematical insights of MiRCo also in comparison with other popular contrast measures.
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Pawar M, Talbar S. Local entropy maximization based image fusion for contrast enhancement of mammogram. JOURNAL OF KING SAUD UNIVERSITY - COMPUTER AND INFORMATION SCIENCES 2021. [DOI: 10.1016/j.jksuci.2018.02.008] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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10
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Low-Light Image Enhancement Based on Quasi-Symmetric Correction Functions by Fusion. Symmetry (Basel) 2020. [DOI: 10.3390/sym12091561] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
Sometimes it is very difficult to obtain high-quality images because of the limitations of image-capturing devices and the environment. Gamma correction (GC) is widely used for image enhancement. However, traditional GC perhaps cannot preserve image details and may even reduce local contrast within high-illuminance regions. Therefore, we first define two couples of quasi-symmetric correction functions (QCFs) to solve these problems. Moreover, we propose a novel low-light image enhancement method based on proposed QCFs by fusion, which combines a globally-enhanced image by QCFs and a locally-enhanced image by contrast-limited adaptive histogram equalization (CLAHE). A large number of experimental results showed that our method could significantly enhance the detail and improve the contrast of low-light images. Our method also has a better performance than other state-of-the-art methods in both subjective and objective assessments.
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Fahim MANI, Jung HY. Fast Single-Image HDR Tone-Mapping by Avoiding Base Layer Extraction. SENSORS (BASEL, SWITZERLAND) 2020; 20:E4378. [PMID: 32764451 PMCID: PMC7472342 DOI: 10.3390/s20164378] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/08/2020] [Revised: 07/31/2020] [Accepted: 07/31/2020] [Indexed: 11/16/2022]
Abstract
The tone-mapping algorithm compresses the high dynamic range (HDR) information into the standard dynamic range for regular devices. An ideal tone-mapping algorithm reproduces the HDR image without losing any vital information. The usual tone-mapping algorithms mostly deal with detail layer enhancement and gradient-domain manipulation with the help of a smoothing operator. However, these approaches often have to face challenges with over enhancement, halo effects, and over-saturation effects. To address these challenges, we propose a two-step solution to perform a tone-mapping operation using contrast enhancement. Our method improves the performance of the camera response model by utilizing the improved adaptive parameter selection and weight matrix extraction. Experiments show that our method performs reasonably well for overexposed and underexposed HDR images without producing any ringing or halo effects.
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Affiliation(s)
| | - Ho Yub Jung
- Department of Computer Engineering, Chosun University, Gwangju 61452, Korea;
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12
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Wang W, Zhang C, Ng MK. Variational model for simultaneously image denoising and contrast enhancement. OPTICS EXPRESS 2020; 28:18751-18777. [PMID: 32672170 DOI: 10.1364/oe.28.018751] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/29/2019] [Accepted: 12/01/2019] [Indexed: 06/11/2023]
Abstract
The performance of contrast enhancement is degraded when input images are noisy. In this paper, we propose and develop a variational model for simultaneously image denoising and contrast enhancement. The idea is to propose a variational approach containing an energy functional to adjust the pixel values of an input image directly so that the resulting histogram can be redistributed to be uniform and the noise of the image can be removed. In the proposed model, a histogram equalization term is considered for image contrast enhancement, a total variational term is incorporate to remove the noise of the input image, and a fidelity term is added to keep the structure and the texture of the input image. The existence of the minimizer and the convergence of the proposed algorithm are studied and analyzed. Experimental results are presented to show the effectiveness of the proposed model compared with existing methods in terms of several measures: average local contrast, discrete entropy, structural similarity index, measure of enhancement, absolute measure of enhancement, and second derivative like measure of enhancement.
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14
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MID Filter: An Orientation-Based Nonlinear Filter For Reducing Multiplicative Noise. ELECTRONICS 2019. [DOI: 10.3390/electronics8090936] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
In this study, an edge-preserving nonlinear filter is proposed to reduce multiplicative noise by using a filter structure based on mathematical morphology. This method is called the minimum index of dispersion (MID) filter. MID is an improved and extended version of MCV (minimum coefficient of variation) and MLV (mean least variance) filters. Different from these filters, this paper proposes an extra-layer for the value-and-criterion function in which orientation information is employed in addition to the intensity information. Furthermore, the selection function is re-modeled by performing low-pass filtering (mean filtering) to reduce multiplicative noise. MID outputs are benchmarked with the outputs of MCV and MLV filters in terms of structural similarity index (SSIM), peak signal-to-noise ratio (PSNR), mean squared error (MSE), standard deviation, and contrast value metrics. Additionally, F Score, which is a hybrid metric that is the combination of all five of those metrics, is presented in order to evaluate all the filters. Experimental results and extensive benchmarking studies show that the proposed method achieves promising results better than conventional MCV and MLV filters in terms of robustness in both edge preservation and noise removal. Noise filter methods normally cannot give better results in noise removal and edge-preserving at the same time. However, this study proves a great contribution that MID filter produces better results in both noise cleaning and edge preservation.
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15
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Ngo HH, Nguyen CH, Nguyen VQ. Multichannel image contrast enhancement based on linguistic rule-based intensificators. Appl Soft Comput 2019. [DOI: 10.1016/j.asoc.2018.12.034] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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17
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Li G. Image Contrast Enhancement Algorithm Based on GM(1,1) and Power Exponential Dynamic Decision. INT J PATTERN RECOGN 2017. [DOI: 10.1142/s0218001418540022] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Image enhancement processing is a very important operation during image preprocessing. Compared with to enhancc the overall contrast level of image, enhancing the local contrast of image can improve the level of such contrast directly as well as the quality and effect of image enhancement. In this paper, the gray prediction model is applied to the process of enhancing image local contrast, so as to measure the change range of image local contrast and adaptively adjust the scale of enhancing image local contrast. The simulation results show that, in addition to enhancing the contrast of gray level on the edge of image, the proposed algorithm can inhibit roughened nonedge region and improve the quality of local enhancement processing, which create a more favorable condition for the further image edge detection.
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Affiliation(s)
- Gang Li
- School of Science, Hubei University of Technology, Wuhan 430068, Hubei, P. R. China
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18
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Maurya L, Mahapatra PK, Kumar A. A social spider optimized image fusion approach for contrast enhancement and brightness preservation. Appl Soft Comput 2017. [DOI: 10.1016/j.asoc.2016.10.012] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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19
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Saleem A, Beghdadi A, Boashash B. A distortion-free contrast enhancement technique based on a perceptual fusion scheme. Neurocomputing 2017. [DOI: 10.1016/j.neucom.2016.11.044] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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20
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Woods M, Katsaggelos AK. Spatial-frequency-based metric for image superresolution. JOURNAL OF THE OPTICAL SOCIETY OF AMERICA. A, OPTICS, IMAGE SCIENCE, AND VISION 2015; 32:2002-2020. [PMID: 26560915 DOI: 10.1364/josaa.32.002002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Abstract
The image processing technique known as superresolution (SR) has the potential to allow engineers to specify lower resolution and, therefore, less expensive cameras for a given task by enhancing the base camera's resolution. This is especially true in the remote detection and classification of objects in the environment, such as aircraft or human faces. Performing each of these tasks requires a minimum image "sharpness" which is quantified by a maximum resolvable spatial frequency, which is, in turn, a function of the camera optics, pixel sampling density, and signal-to-noise ratio. Much of the existing SR literature focuses on SR performance metrics for candidate algorithms, such as perceived image quality or peak SNR. These metrics can be misleading because they also credit deblurring and/or denoising in addition to true SR. In this paper, we propose a new, task-based metric where the performance of an SR algorithm is, instead, directly tied to the probability of successfully detecting critical spatial frequencies within the scene.
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21
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Computer assisted diagnostic system in tumor radiography. J Med Syst 2013; 37:9938. [PMID: 23504472 DOI: 10.1007/s10916-013-9938-3] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2013] [Accepted: 03/06/2013] [Indexed: 10/27/2022]
Abstract
An improved and efficient method is presented in this paper to achieve a better trade-off between noise removal and edge preservation, thereby detecting the tumor region of MRI brain images automatically. Compass operator has been used in the fourth order Partial Differential Equation (PDE) based denoising technique to preserve the anatomically significant information at the edges. A new morphological technique is also introduced for stripping skull region from the brain images, which consequently leading to the process of detecting tumor accurately. Finally, automatic seeded region growing segmentation based on an improved single seed point selection algorithm is applied to detect the tumor. The method is tested on publicly available MRI brain images and it gives an average PSNR (Peak Signal to Noise Ratio) of 36.49. The obtained results also show detection accuracy of 99.46%, which is a significant improvement than that of the existing results.
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Huang SC, Cheng FC, Chiu YS. Efficient contrast enhancement using adaptive gamma correction with weighting distribution. IEEE TRANSACTIONS ON IMAGE PROCESSING : A PUBLICATION OF THE IEEE SIGNAL PROCESSING SOCIETY 2013; 22:1032-41. [PMID: 23144035 DOI: 10.1109/tip.2012.2226047] [Citation(s) in RCA: 131] [Impact Index Per Article: 11.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/10/2023]
Abstract
This paper proposes an efficient method to modify histograms and enhance contrast in digital images. Enhancement plays a significant role in digital image processing, computer vision, and pattern recognition. We present an automatic transformation technique that improves the brightness of dimmed images via the gamma correction and probability distribution of luminance pixels. To enhance video, the proposed image-enhancement method uses temporal information regarding the differences between each frame to reduce computational complexity. Experimental results demonstrate that the proposed method produces enhanced images of comparable or higher quality than those produced using previous state-of-the-art methods.
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Affiliation(s)
- Shih-Chia Huang
- Department of Electronic Engineering, National Taipei University of Technology, Taipei 106, Taiwan.
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23
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Rivera AR, Ryu B, Chae O. Content-aware dark image enhancement through channel division. IEEE TRANSACTIONS ON IMAGE PROCESSING : A PUBLICATION OF THE IEEE SIGNAL PROCESSING SOCIETY 2012; 21:3967-3980. [PMID: 22588591 DOI: 10.1109/tip.2012.2198667] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/31/2023]
Abstract
The current contrast enhancement algorithms occasionally result in artifacts, overenhancement, and unnatural effects in the processed images. These drawbacks increase for images taken under poor illumination conditions. In this paper, we propose a content-aware algorithm that enhances dark images, sharpens edges, reveals details in textured regions, and preserves the smoothness of flat regions. The algorithm produces an ad hoc transformation for each image, adapting the mapping functions to each image's characteristics to produce the maximum enhancement. We analyze the contrast of the image in the boundary and textured regions, and group the information with common characteristics. These groups model the relations within the image, from which we extract the transformation functions. The results are then adaptively mixed, by considering the human vision system characteristics, to boost the details in the image. Results show that the algorithm can automatically process a wide range of images-e.g., mixed shadow and bright areas, outdoor and indoor lighting, and face images-without introducing artifacts, which is an improvement over many existing methods.
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Affiliation(s)
- Adin Ramirez Rivera
- Department of Computer Engineering, Kyung Hee University, Gyeonggido, South Korea.
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Liu WM, Maivelett J, Kato GJ, Taylor JG, Yang WC, Liu YC, Yang YG, Gorbach AM. Reconstruction of Thermographic Signals to Map Perforator Vessels in Humans. QUANTITATIVE INFRARED THERMOGRAPHY JOURNAL 2012; 9:123-133. [PMID: 23667389 PMCID: PMC3650860 DOI: 10.1080/17686733.2012.737157] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/02/2023]
Abstract
Thermal representations on the surface of a human forearm of underlying perforator vessels have previously been mapped via recovery-enhanced infrared imaging, which is performed as skin blood flow recovers to baseline levels following cooling of the forearm. We noted that the same vessels could also be observed during reactive hyperaemia tests after complete 5-min occlusion of the forearm by an inflatable cuff. However, not all subjects showed vessels with acceptable contrast. Therefore, we applied a thermographic signal reconstruction algorithm to reactive hyperaemia testing, which substantially enhanced signal-to-noise ratios between perforator vessels and their surroundings, thereby enabling their mapping with higher accuracy and a shorter occlusion period.
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Affiliation(s)
- Wei-Min Liu
- Dept. of Computer Science and Information Engineering, National Chung Cheng University, Taiwan
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Celik T, Tjahjadi T. Automatic image equalization and contrast enhancement using Gaussian mixture modeling. IEEE TRANSACTIONS ON IMAGE PROCESSING : A PUBLICATION OF THE IEEE SIGNAL PROCESSING SOCIETY 2012; 21:145-156. [PMID: 21775265 DOI: 10.1109/tip.2011.2162419] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/31/2023]
Abstract
In this paper, we propose an adaptive image equalization algorithm that automatically enhances the contrast in an input image. The algorithm uses the Gaussian mixture model to model the image gray-level distribution, and the intersection points of the Gaussian components in the model are used to partition the dynamic range of the image into input gray-level intervals. The contrast equalized image is generated by transforming the pixels' gray levels in each input interval to the appropriate output gray-level interval according to the dominant Gaussian component and the cumulative distribution function of the input interval. To take account of the hypothesis that homogeneous regions in the image represent homogeneous silences (or set of Gaussian components) in the image histogram, the Gaussian components with small variances are weighted with smaller values than the Gaussian components with larger variances, and the gray-level distribution is also used to weight the components in the mapping of the input interval to the output interval. Experimental results show that the proposed algorithm produces better or comparable enhanced images than several state-of-the-art algorithms. Unlike the other algorithms, the proposed algorithm is free of parameter setting for a given dynamic range of the enhanced image and can be applied to a wide range of image types.
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Affiliation(s)
- Turgay Celik
- School of Engineering, University ofWarwick, Coventry, UK.
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ADEL MOULOUD, ZUWALA DANIEL, RASIGNI MONIQUE, BOURENNANE SALAH. ENHANCEMENT OF MAMMOGRAPHIC PHANTOM FEATURES BY NOISE REDUCTION. INT J PATTERN RECOGN 2011. [DOI: 10.1142/s0218001407005788] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
A noise reduction scheme on digitized mammographic phantom images is presented. This algorithm is based on a direct contrast modification method with an optimal function, obtained by using the mean squared error as a criterion. Computer simulated images containing objects similar to those observed in the phantom are built to evaluate the performance of the algorithm. Noise reduction results obtained on both simulated and real phantom images show that the developed method may be considered as a good preprocessing step from the point of view of automating phantom film evaluation by means of image processing.
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Affiliation(s)
- MOULOUD ADEL
- Institut FRESNEL, UMR-CNRS 6133, Equipe GSM, France
| | - DANIEL ZUWALA
- Interface Physique-Biologie-Médecine, case EC1, Domaine Universitaire de Saint-Jérôme, 13397 Marseille Cedex 20, France
| | - MONIQUE RASIGNI
- Interface Physique-Biologie-Médecine, case EC1, Domaine Universitaire de Saint-Jérôme, 13397 Marseille Cedex 20, France
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Li G, Tong Y, Xiao X. Adaptive Fuzzy Enhancement Algorithm of Surface Image based on Local Discrimination via Grey Entropy. ACTA ACUST UNITED AC 2011. [DOI: 10.1016/j.proeng.2011.08.296] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/14/2022]
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29
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Murakoshi K, Miura M. Image correction method for the colour contrast effect using inverse processes of the brain. Biosystems 2010; 101:162-6. [PMID: 20599583 DOI: 10.1016/j.biosystems.2010.06.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2010] [Revised: 06/17/2010] [Accepted: 06/18/2010] [Indexed: 10/19/2022]
Abstract
In the colour contrast effect, the impression of a colour changes according to the situation; cases occur in which the colour appearance is misunderstood. We propose an image signal processing method for preventing such misperception of colour. Many conventional image improving methods emphasize the contrast of images as same as the brain does. However, by their processes, the colour contrast effect is not canceled; we misunderstand the colour. The objective of this study is to perceive original colour. Therefore, we propose an image correction method using inverse processes of the brain in order to cancel the processes of the brain, the colour contrast effect. We verified whether the proposed method corrected the colour contrast effect by conducting a psychological experiment. The results show that the method succeeds in canceling the colour contrast effect.
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Affiliation(s)
- Kazushi Murakoshi
- Department of Computer Science and Engineering, Toyohashi University of Technology, 1-1 Hibarigaoka, Tenpaku-cho, Toyohashi 441-8580, Japan.
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30
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Arici T, Dikbas S, Altunbasak Y. A histogram modification framework and its application for image contrast enhancement. IEEE TRANSACTIONS ON IMAGE PROCESSING : A PUBLICATION OF THE IEEE SIGNAL PROCESSING SOCIETY 2009; 18:1921-35. [PMID: 19403363 DOI: 10.1109/tip.2009.2021548] [Citation(s) in RCA: 93] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
A general framework based on histogram equalization for image contrast enhancement is presented. In this framework, contrast enhancement is posed as an optimization problem that minimizes a cost function. Histogram equalization is an effective technique for contrast enhancement. However, a conventional histogram equalization (HE) usually results in excessive contrast enhancement, which in turn gives the processed image an unnatural look and creates visual artifacts. By introducing specifically designed penalty terms, the level of contrast enhancement can be adjusted; noise robustness, white/black stretching and mean-brightness preservation may easily be incorporated into the optimization. Analytic solutions for some of the important criteria are presented. Finally, a low-complexity algorithm for contrast enhancement is presented, and its performance is demonstrated against a recently proposed method.
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Affiliation(s)
- Tarik Arici
- Department of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA.
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31
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Papadopoulos A, Fotiadis DI, Costaridou L. Improvement of microcalcification cluster detection in mammography utilizing image enhancement techniques. Comput Biol Med 2008; 38:1045-55. [PMID: 18774128 DOI: 10.1016/j.compbiomed.2008.07.006] [Citation(s) in RCA: 84] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2006] [Revised: 06/02/2008] [Accepted: 07/09/2008] [Indexed: 11/28/2022]
Abstract
In this work, the effect of an image enhancement processing stage and the parameter tuning of a computer-aided detection (CAD) system for the detection of microcalcifications in mammograms is assessed. Five (5) image enhancement algorithms were tested introducing the contrast-limited adaptive histogram equalization (CLAHE), the local range modification (LRM) and the redundant discrete wavelet (RDW) linear stretching and shrinkage algorithms. CAD tuning optimization was targeted to the percentage of the most contrasted pixels and the size of the minimum detectable object which could satisfactorily represent a microcalcification. The highest performance in two mammographic datasets, were achieved for LRM (A(Z)=0.932) and the wavelet-based linear stretching (A(Z)=0.926) methodology.
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Affiliation(s)
- A Papadopoulos
- Department of Medical Physics, Medical School, University of Ioannina, GR 45110 Ioannina, Greece
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32
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Panetta KA, Wharton EJ, Agaian SS. Human visual system-based image enhancement and logarithmic contrast measure. ACTA ACUST UNITED AC 2008; 38:174-88. [PMID: 18270089 DOI: 10.1109/tsmcb.2007.909440] [Citation(s) in RCA: 187] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Varying scene illumination poses many challenging problems for machine vision systems. One such issue is developing global enhancement methods that work effectively across the varying illumination. In this paper, we introduce two novel image enhancement algorithms: edge-preserving contrast enhancement, which is able to better preserve edge details while enhancing contrast in images with varying illumination, and a novel multihistogram equalization method which utilizes the human visual system (HVS) to segment the image, allowing a fast and efficient correction of nonuniform illumination. We then extend this HVS-based multihistogram equalization approach to create a general enhancement method that can utilize any combination of enhancement algorithms for an improved performance. Additionally, we propose new quantitative measures of image enhancement, called the logarithmic Michelson contrast measure (AME) and the logarithmic AME by entropy. Many image enhancement methods require selection of operating parameters, which are typically chosen using subjective methods, but these new measures allow for automated selection. We present experimental results for these methods and make a comparison against other leading algorithms.
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Affiliation(s)
- Karen A Panetta
- Department of Electrical and Computer Engineering, Tufts University, Medford, MA 02155, USA.
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33
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Spine localization in X-ray images using interest point detection. J Digit Imaging 2008; 22:309-18. [PMID: 18273669 DOI: 10.1007/s10278-007-9099-3] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2007] [Revised: 11/16/2007] [Accepted: 12/20/2007] [Indexed: 10/22/2022] Open
Abstract
This study was conducted to evaluate a new method used to calculate vertebra orientation in medical x-ray images. The goal of this work is to develop an x-ray image segmentation approach used to identify the location and the orientation of the cervical vertebrae in medical images. We propose a method for localization of vertebrae by extracting the anterior-left-faces of vertebra contours. This approach is based on automatic corner points of interest detection. For this task, we use the Harris corner detector. The final goal is to determine vertebral motion induced by their movement between two or several positions. The proposed system proceeds in several phases as follows: (a) image acquisition, (b) corner detection, (c) extracting of the corners belonging to vertebra left sides, (d) global estimation of the spine curvature, and (e) anterior face vertebra detection.
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Agaian SS, Silver B, Panetta KA. Transform coefficient histogram-based image enhancement algorithms using contrast entropy. IEEE TRANSACTIONS ON IMAGE PROCESSING : A PUBLICATION OF THE IEEE SIGNAL PROCESSING SOCIETY 2007; 16:741-58. [PMID: 17357734 DOI: 10.1109/tip.2006.888338] [Citation(s) in RCA: 75] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/14/2023]
Abstract
Many applications of histograms for the purposes of image processing are well known. However, applying this process to the transform domain by way of a transform coefficient histogram has not yet been fully explored. This paper proposes three methods of image enhancement: a) logarithmic transform histogram matching, b) logarithmic transform histogram shifting, and c) logarithmic transform histogram shaping using Gaussian distributions. They are based on the properties of the logarithmic transform domain histogram and histogram equalization. The presented algorithms use the fact that the relationship between stimulus and perception is logarithmic and afford a marriage between enhancement qualities and computational efficiency. A human visual system-based quantitative measurement of image contrast improvement is also defined. This helps choose the best parameters and transform for each enhancement. A number of experimental results are presented to illustrate the performance of the proposed algorithms.
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Affiliation(s)
- Sos S Agaian
- College of Engineering, University of Texas at San Antonio, San Antonio, TX 78249-0669, USA.
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35
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Lee S. Content-based image enhancement in the compressed domain based on multi-scale α-rooting algorithm. Pattern Recognit Lett 2006. [DOI: 10.1016/j.patrec.2005.12.004] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
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36
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Matz SC, de Figueiredo RJP. A nonlinear image contrast sharpening approach based on Munsell's scale. IEEE TRANSACTIONS ON IMAGE PROCESSING : A PUBLICATION OF THE IEEE SIGNAL PROCESSING SOCIETY 2006; 15:900-9. [PMID: 16579377 DOI: 10.1109/tip.2005.863935] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2023]
Abstract
Contrast is a measure of the variation in intensity or gray value in a specified region of an image. The region can be most or all of the image, giving rise to a global concept of contrast. The region might, on the other hand, be a small window in which case the concept of contrast is a locally defined expression. In this work, we introduce a nonlinear local contrast enhancement method. This method utilizes the Munsell value scale which is based upon human visual perception. Use of the Munsell value scale allows for the partitioning of the gray scale into ten discrete subintervals. Subsequent local processing occurs within each of these subintervals. Inside each subinterval, this method constructs a contrast enhancement function that is a smooth approximation to the threshold step function and which maps a given subinterval into itself. This function then thresholds the gray values in a subinterval in a smooth manner about a locally computed quantity called the mean edge gray value. By enhancing the contrast in this way, the original shades of gray are preserved. That is, the groupings of the gray values by subinterval are preserved. As a result, no gray value distortion is introduced into the image.
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37
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Tang J, Kim J, Peli E. Image enhancement in the JPEG domain for people with vision impairment. IEEE Trans Biomed Eng 2004; 51:2013-23. [PMID: 15536903 DOI: 10.1109/tbme.2004.834264] [Citation(s) in RCA: 65] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
An image enhancement algorithm for low-vision patients was developed for images compressed using the JPEG standard. The proposed algorithm enhances the images in the discrete cosine transform domain by weighting the quantization table in the decoder. Our specific implementation increases the contrast at all bands of frequencies by an equal factor. The enhancement algorithm has four advantages: 1) low computational cost; 2) suitability for real-time application; 3) ease of adjustment by end-users (for example, adjusting a single parameter); and 4) less severe block artifacts as compared with conventional (post compression) enhancements. Experiments with visually impaired patients show improved perceived image quality at moderate levels of enhancement but rejection of artifacts caused by higher levels of enhancement.
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Affiliation(s)
- Jinshan Tang
- Schepens Eye Research Institute, Harvard Medical School, Boston, MA 02114-2500, USA.
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38
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Wang YP, Wu Q, Castleman KR, Xiong Z. Chromosome image enhancement using multiscale differential operators. IEEE TRANSACTIONS ON MEDICAL IMAGING 2003; 22:685-693. [PMID: 12846437 DOI: 10.1109/tmi.2003.812255] [Citation(s) in RCA: 13] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
Chromosome banding patterns are very important features for karyotyping, based on which cytogenetic diagnosis procedures are conducted. Due to cell culture, staining, and imaging conditions, image enhancement is a desirable preprocessing step before performing chromosome classification. In this paper, we apply a family of differential wavelet transforms (Wang and Lee, 1998), (Wang, 1999) for this purpose. The proposed differential filters facilitate the extraction of multiscale geometric features of chromosome images. Moreover, desirable fast computation can be realized. We study the behavior of both banding edge pattern and noise in the wavelet transform domain. Based on the fact that image geometrical features like edges are correlated across different scales in the wavelet representation, a multiscale point-wise product (MPP) is used to characterize the correlation of the image features in the scale-space. A novel algorithm is proposed for the enhancement of banding patterns in a chromosome image. In order to compare objectively the performance of the proposed algorithm against several existing image-enhancement techniques, a quantitative criteria, the contrast improvement ratio (CIR), has been adopted to evaluate the enhancement results. The experimental results indicate that the proposed method consistently outperforms existing techniques in terms of the CIR measure, as well as in visual effect. The effect of enhancement on cytogenetic diagnosis is further investigated by classification tests conducted prior to and following the chromosome image enhancement. In comparison with conventional techniques, the proposed method leads to better classification results, thereby benefiting the subsequent cytogenetic diagnosis.
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Affiliation(s)
- Yu-Ping Wang
- Advanced Digital Imaging Research, LLC., 2525 South Shore Blvd., Suite 100, League City, TX 77573, USA.
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39
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40
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Ozanian TO, Phillips R. Enhancement of fluoroscopic images with varying contrast. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2001; 65:1-16. [PMID: 11223147 DOI: 10.1016/s0169-2607(00)00104-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/23/2023]
Abstract
A heuristic algorithm for enhancement of fluoroscopic images of varying contrast is proposed. The new technique aims at identifying a suitable type of enhancement for different locations in an image. The estimation relies on simple preliminary classification of image parts into one of the following types: uniform, sharp (with sufficient contrast), detail-containing (structure present) and unknown (for the cases where it is difficult to make a decision). Different smoothing techniques are applied locally in the different types of image parts. For those parts that are classified as detail-containing, probable object boundaries are identified and local sharpening is carried out to increase the contrast at these places. The adopted approach attempts to improve the quality of an image by reducing available noise and simultaneously increasing the contrast at probable object boundaries without increasing the overall dynamic range. In addition, it allows noise to be cleaned, that at some locations is stronger than the fine structure at other locations, whilst preserving the details.
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Affiliation(s)
- T O Ozanian
- Department of Computer Science, University of Hull, Hull HU6 7RX, UK
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41
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Agaian SS, Panetta K, Grigoryan AM. Transform-based image enhancement algorithms with performance measure. IEEE TRANSACTIONS ON IMAGE PROCESSING : A PUBLICATION OF THE IEEE SIGNAL PROCESSING SOCIETY 2001; 10:367-382. [PMID: 18249627 DOI: 10.1109/83.908502] [Citation(s) in RCA: 41] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/25/2023]
Abstract
This paper presents a new class of the "frequency domain"-based signal/image enhancement algorithms including magnitude reduction, log-magnitude reduction, iterative magnitude and a log-reduction zonal magnitude technique. These algorithms are described and applied for detection and visualization of objects within an image. The new technique is based on the so-called sequency ordered orthogonal transforms, which include the well-known Fourier, Hartley, cosine, and Hadamard transforms, as well as new enhancement parametric operators. A wide range of image characteristics can be obtained from a single transform, by varying the parameters of the operators. We also introduce a quantifying method to measure signal/image enhancement called EME. This helps choose the best parameters and transform for each enhancement. A number of experimental results are presented to illustrate the performance of the proposed algorithms.
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Affiliation(s)
- S S Agaian
- Division of Engineering, The University of Texas, San Antonio, TX 78249-0669, USA.
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42
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Optimizing Edge Detectors for Robust Automatic Threshold Selection: Coping with Edge Curvature and Noise. ACTA ACUST UNITED AC 1998. [DOI: 10.1006/gmip.1998.0478] [Citation(s) in RCA: 37] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
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43
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Kim JK, Park JM, Song KS, Park HW. Adaptive mammographic image enhancement using first derivative and local statistics. IEEE TRANSACTIONS ON MEDICAL IMAGING 1997; 16:495-502. [PMID: 9368105 DOI: 10.1109/42.640739] [Citation(s) in RCA: 27] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2023]
Abstract
This paper proposes an adaptive image enhancement method for mammographic images, which is based on the first derivative and the local statistics. The adaptive enhancement method consists of three processing steps. The first step is to remove the film artifacts which may be misread as microcalcifications. The second step is to compute the gradient images by using the first derivative operators. The third step is to enhance the important features of the mammographic image by adding the adaptively weighted gradient images. Local statistics of the image are utilized for adaptive realization of the enhancement, so that image details can be enhanced and image noises can be suppressed. The objective performances of the proposed method were compared with those by the conventional image enhancement methods for a simulated image and the seven mammographic images containing real microcalcifications. The performance of the proposed method was also evaluated by means of the receiver operating-characteristics (ROC) analysis for 78 real mammographic images with and without microcalcifications.
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Affiliation(s)
- J K Kim
- Department of Information and Communication Engineering, Korea Advanced Institute of Science and Technology, Dongdaemungu, Seoul, Korea
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44
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Bonnet N, Vautrot P. Image Analysis: Is the Fourier Transform Becoming Obsolete? ACTA ACUST UNITED AC 1997. [DOI: 10.1051/mmm:1997106] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
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45
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Coker DA, Torquato S, Dunsmuir JH. Morphology and physical properties of Fontainebleau sandstone via a tomographic analysis. ACTA ACUST UNITED AC 1996. [DOI: 10.1029/96jb00811] [Citation(s) in RCA: 111] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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46
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Karras T, Wilson DC, Geiser EA, Conetta DA. Automatic identification of papillary muscles in left-ventricular short-axis echocardiographic images. IEEE Trans Biomed Eng 1996; 43:460-70. [PMID: 8849459 DOI: 10.1109/10.488794] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
Abstract
An automatic method for identifying the location of the papillary muscles in two-dimensional (2-D) short-axis echocardiographic images is described. The technique uses both spatial and temporal information to identify the presence and track the location of the muscles in the left ventricle from end-diastole to end-systole. The three main steps of the method are spatial preprocessing, spatial processing, and temporal processing. The spatial preprocessing step includes a region of search estimation. The spatial processing step includes a papillary muscle existence test and an initial approximation of the papillary muscle points. The temporal processing includes motion-pattern evaluation and final papillary muscle location. The estimates of existence and position for the automatic method were compared with estimates made by an independent expert observer. Two hundred and ten frames, three taken from each of 70 image sequences, were evaluated. Since two regions of search were processed for each frame (one for the posterior-inferior and one for the anterior-lateral papillary muscle), a total of 420 approximations were made. Of this total, 340 automatic estimates were judged to be in close agreement with estimates made by the expert. Of the remaining 80 approximations, 54 estimates were made by the expert when the computer determined that no papillary muscle was present, 17 estimates provided poor results, and nine estimates were made by the computer when the observer concluded that no papillary muscle was present.
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Affiliation(s)
- T Karras
- Division of Cardiology, University of Florida, College of Medicine, Gainesville 32610-0277, USA
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47
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Lindquist WB, Lee SM, Coker DA, Jones KW, Spanne P. Medial axis analysis of void structure in three-dimensional tomographic images of porous media. ACTA ACUST UNITED AC 1996. [DOI: 10.1029/95jb03039] [Citation(s) in RCA: 359] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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48
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Laine A, Jian Fan, Wuhai Yang. Wavelets for contrast enhancement of digital mammography. ACTA ACUST UNITED AC 1995. [DOI: 10.1109/51.464770] [Citation(s) in RCA: 149] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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49
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Image Enhancement. ACTA ACUST UNITED AC 1995. [DOI: 10.1016/s1076-5670(08)70006-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register]
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50
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Lozanoff S, Zingeser MR, Diewert VM. Computerized modelling of nasal capsular morphogenesis in prenatal primates. Clin Anat 1993. [DOI: 10.1002/ca.980060107] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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