Extended focused imaging and depth map reconstruction in optical scanning holography

Refocus criterion from image-plane speckle correlation in digital holographic interferometry

In digital holography and holographic interferometry, refocusing to the correct image plane can be challenging and may be obtained by various metrics. This paper proposes a digital refocus approach utilizing the linear relationship between in-plane speckle motion and defocus as a response to an induced phase gradient. The theory based on cross-correlations between pairs of intensity images reconstructed at different distances from the recording plane is discussed. Two simple metrics, based on the cross-correlation properties of the reconstructed speckle images, are proposed and evaluated utilizing both simulations and experiments. Experiments exhibit similar trends in which the estimate of the correct reconstruction distance differs by a small amount between the two metrics. The difference is found less than 1% in the estimate of the true reconstruction distance. The results show that either metric is able to yield a sufficient reconstruction distance for the reconstruction of the image plane.

Hough transform-based multi-object autofocusing compressive holography

Reconstruction of multiple objects from one hologram can be affected by the focus metric judgment of autofocusing. Various segmentation algorithms are applied to obtain a single object in the hologram. Each object is unambiguously reconstructed to acquire its focal position, which produces complicated calculations. Herein, Hough transform (HT)-based multi-object autofocusing compressive holography is presented. The sharpness of each reconstructed image is computed by using a focus metric such as entropy or variance. According to the characteristics of the object, the standard HT is further used for calibration to remove redundant extreme points. The compressive holographic imaging framework with a filter layer can eliminate the inherent noise in in-line reconstruction including cross talk noise of different depth layers, two-order noise, and twin image noise. The proposed method can effectively obtain 3D information on multiple objects and achieve noise elimination by only reconstructing from one hologram.

Extension of refocus depth range in digital holographic microscopy

Digital holographic microscopy (DHM) suffers from a limited refocus depth range due to the employed microscope objective. The relationship between the refocus depth range of the DHM system and its optical parameters is studied theoretically and experimentally, and a method is proposed that combines wavefront coding with bicubic interpolation and extrapolation iteration to extend the refocus depth range. For obtaining a uniform point spread function on the refocus plane, a propagator kernel in numerical reconstruction is multiplied by a numerical logarithmic phase mask, and a deviation of the refocus distance is made. To improve the resolution of the refocused image, the size of the hologram is doubly enlarged. This approach can extend the refocus depth range from 0.9 up to 1.5 mm. This work provides important guidance for high-resolution imaging with a large refocus depth range in DHM.

Acceleration of autofocusing with improved edge extraction using structure tensor and Schatten norm

Determining the optimal focal plane amongst a stack of blurred images in a short response time is a non-trivial task in optical imaging like microscopy and photography. An autofocusing algorithm, or in other words, a focus metric, is key to effectively dealing with such problem. In previous work, we proposed a structure tensor-based autofocusing algorithm for coherent imaging, i.e., digital holography. In this paper, we further extend the realm of this method in more imaging modalities. With an optimized computation scheme of structure tensor, a significant acceleration of about fivefold in computation speed without sacrificing the autofocusing accuracy is achieved by using the Schatten matrix norm instead of the vector norm. Besides, we also demonstrate its edge extraction capability by retrieving the intermediate tensor image. Synthesized and experimental data acquired in various imaging scenarios such as incoherent microscopy and photography are demonstrated to verify the efficacy of this method.

Characterization of Spatial Light Modulator Based on the Phase in Fourier Domain of the Hologram and Its Applications in Coherent Imaging

Although digital holography is used widely at present, the information contained in the digital hologram is still underutilized. For example, the phase values of the Fourier spectra of the hologram are seldom used directly. In this paper, we take full advantage of them for characterizing the phase modulation of a spatial light modulator (SLM). Incident plane light beam is divided into two beams, one of which passes the SLM and interferes with the other one. If an image with a single grey scale loads on the SLM, theoretical analysis proves that the phase of the Fourier spectra of the obtained hologram contains the added phase and a constant part relative to the optical distance. By subtracting the phase for the image with the grey scale of 0 from that for the image with other grey scales, the phase modulation can be characterized. Simulative and experimental results validate that the method is effective. The SLM after characterization is successfully used for coherent imaging, which reconfirms that this method is exact in practice. When compared to the traditional method, the new method is much faster and more convenient.

Fast and robust Fourier domain-based classification for on-chip lens-free flow cytometry

The development of portable haematology analysers receives increased attention due to their deployability in resource-limited or emergency settings. Lens-free in-line holographic microscopy is one of the technologies that is being pushed forward in this regard as it eliminates complex and expensive optics, making miniaturisation and integration with microfluidics possible. On-chip flow cytometry enables high-speed capturing of individual cells in suspension, giving rise to high-throughput cell counting and classification. To perform a real-time analysis on this high-throughput content, we propose a fast and robust framework for the classification of leukocytes. The raw data consists of holographic acquisitions of leukocytes, captured with a high-speed camera as they are flowing through a microfluidic chip. Three different types of leukocytes are considered: granulocytes, monocytes and T-lymphocytes. The proposed method bypasses the reconstruction of the holographic data altogether by extracting Zernike moments directly from the frequency domain. By doing so, we introduce robustness to translations and rotations of cells, as well as to changes in distance of a cell with respect to the image sensor, achieving classification accuracies up to 96.8%. Furthermore, the reduced computational complexity of this approach, compared to traditional frameworks that involve the reconstruction of the holographic data, allows for very fast processing and classification, making it applicable in high-throughput flow cytometry setups.

Accurate label-free 3-part leukocyte recognition with single cell lens-free imaging flow cytometry

Three-part white blood cell differentials which are key to routine blood workups are typically performed in centralized laboratories on conventional hematology analyzers operated by highly trained staff. With the trend of developing miniaturized blood analysis tool for point-of-need in order to accelerate turnaround times and move routine blood testing away from centralized facilities on the rise, our group has developed a highly miniaturized holographic imaging system for generating lens-free images of white blood cells in suspension. Analysis and classification of its output data, constitutes the final crucial step ensuring appropriate accuracy of the system. In this work, we implement reference holographic images of single white blood cells in suspension, in order to establish an accurate ground truth to increase classification accuracy. We also automate the entire workflow for analyzing the output and demonstrate clear improvement in the accuracy of the 3-part classification. High-dimensional optical and morphological features are extracted from reconstructed digital holograms of single cells using the ground-truth images and advanced machine learning algorithms are investigated and implemented to obtain 99% classification accuracy. Representative features of the three white blood cell subtypes are selected and give comparable results, with a focus on rapid cell recognition and decreased computational cost.

New autofocus and reconstruction method based on a connected domain

In this Letter, we propose a new method for auto-focusing and reconstruction without defocus noise in optical scanning holography. By using a connected domain (CD) to calculate the area of different domains, which are labeled by a connected component, the focus distance can be found via the smallest area of each CD. Meanwhile, the sectional images without defocus noise can also be reconstructed based on the labeled domains. The effectiveness of this method has been verified with a simulation and experiments.

Axial localization using time reversal multiple signal classification in optical scanning holography

This paper presents a method to identify the axial location of targets in an optical scanning holography (OSH) system. By combining time reversal (TR) technique with the multiple signal classification (MUSIC) method in OSH, axial location can be detected with high resolution. Both simulation and experimental work have been carried out to verify the feasibility of the proposed work.

Automatic focusing for multisectional objects in digital holography using the structure tensor

Determining the axial position of the recorded object in digital holography is a crucial step for image reconstruction. When multiple discrete sections of a three-dimensional object are overlapping each other, this issue becomes more challenging. In this Letter, an autofocusing algorithm using the structure tensor and its eigenvalues is proposed. This method can extract the focal distance of each section for a multi-sectional object irrespective of whether the sections are overlapping or not. We validate the applicability of the proposed technique with synthesized and experimental data using two types of holographic systems.

Quality assessment of refocus criteria for particle imaging in digital off-axis holography

This paper proposes a quality assessment of focusing criteria for imaging in digital off-axis holography. In the literature, several refocus criteria have been proposed in the past to get the best refocus distance in digital holography. As a general rule, the best focusing plane is determined by the reconstruction distance for which the criterion function presents a maximum or a minimum. To evaluate the robustness of these criteria, 13 criteria are compared with application on both amplitude and phase objects from off-axis holographic data. Simulation and experimental results lead to define a general rule and to exhibit the most robust criteria for accurate and rapid refocusing in digital holography.

Refocus criterion based on maximization of the coherence factor in digital three-wavelength holographic interferometry

This Letter presents an alternative approach for image refocusing in digital Fresnel holography. In the literature, a large majority of reported focus detection criteria is based on amplitude contrast or phase contrast. We propose a focus detection criterion based on the speckle phase coherence factor. This factor reaches its maximum value at the best focus distance. At any reconstruction distance, estimation of the coherence factor is based on robust noise estimation from anisotropic diffusion. We propose a theoretical relation to estimate the coherence factor from the measured standard deviation. Experimental results for the case of three-color holographic imaging and interferometry are provided. Experimental results show the suitability of the proposed approach for image plane refocusing.

Low Complexity Compression and Speed Enhancement for Optical Scanning Holography

In this paper we report a low complexity compression method that is suitable for compact optical scanning holography (OSH) systems with different optical settings. Our proposed method can be divided into 2 major parts. First, an automatic decision maker is applied to select the rows of holographic pixels to be scanned. This process enhances the speed of acquiring a hologram, and also lowers the data rate. Second, each row of down-sampled pixels is converted into a one-bit representation with delta modulation (DM). Existing DM-based hologram compression techniques suffers from the disadvantage that a core parameter, commonly known as the step size, has to be determined in advance. However, the correct value of the step size for compressing each row of hologram is dependent on the dynamic range of the pixels, which could deviate significantly with the object scene, as well as OSH systems with different opical settings. We have overcome this problem by incorporating a dynamic step-size adjustment scheme. The proposed method is applied in the compression of holograms that are acquired with 2 different OSH systems, demonstrating a compression ratio of over two orders of magnitude, while preserving favorable fidelity on the reconstructed images.