Impact of HVS models on model-based halftoning

Efficient Halftoning via Deep Reinforcement Learning

Halftoning aims to reproduce a continuous-tone image with pixels whose intensities are constrained to two discrete levels. This technique has been deployed on every printer, and the majority of them adopt fast methods (e.g., ordered dithering, error diffusion) that fail to render structural details, which determine halftone's quality. Other prior methods of pursuing visual pleasure by searching for the optimal halftone solution, on the contrary, suffer from their high computational cost. In this paper, we propose a fast and structure-aware halftoning method via a data-driven approach. Specifically, we formulate halftoning as a reinforcement learning problem, in which each binary pixel's value is regarded as an action chosen by a virtual agent with a shared fully convolutional neural network (CNN) policy. In the offline phase, an effective gradient estimator is utilized to train the agents in producing high-quality halftones in one action step. Then, halftones can be generated online by one fast CNN inference. Besides, we propose a novel anisotropy suppressing loss function, which brings the desirable blue-noise property. Finally, we find that optimizing SSIM could result in holes in flat areas, which can be avoided by weighting the metric with the contone's contrast map. Experiments show that our framework can effectively train a light-weight CNN, which is 15x faster than previous structure-aware methods, to generate blue-noise halftones with satisfactory visual quality. We also present a prototype of deep multitoning to demonstrate the extensibility of our method.

Digital halftoning method with simultaneously optimized perceptual image quality and drive current for multi-tonal electrophoretic displays

While using digital halftoning to achieve multi-tones in a 1 bit electrophoretic display (EPD), e.g., a three-pigment chromatic EPD, the drive current is significantly increased because of frequently reversed pixel values. Aimed at this issue, this study first establishes a model that can accurately predict the drive current from image content. Next, based on the direct binary search method, a new halftoning method is proposed by constructing a combined merit function that incorporates both the perceptual image quality and the drive current. As a result, in experiments using a 13.5 in. three-pigment EPD and several test images, compared with the well-developed error-diffusion method, the proposed method produces little image quality degradation, whereas the drive current increase with respect to the minimum current of the EPD is reduced from 71.8 to 33.0 mA, for a significant reduction of 54.0%.

Halftone Image Watermarking by Content Aware Double-Sided Embedding Error Diffusion

In this paper, we carry out a performance analysis from a probabilistic perspective to introduce the error diffusion-based halftone visual watermarking (EDHVW) methods' expected performances and limitations. Then, we propose a new general EDHVW method, content aware double-sided embedding error diffusion (CaDEED), via considering the expected watermark decoding performance with specific content of the cover images and watermark, different noise tolerance abilities of various cover image content, and the different importance levels of every pixel (when being perceived) in the secret pattern (watermark). To demonstrate the effectiveness of CaDEED, we propose CaDEED with expectation constraint (CaDEED-EC) and CaDEED-noise visibility function (NVF) and importance factor (IF) (CaDEED-N&I). Specifically, we build CaDEED-EC by only considering the expected performances of specific cover images and watermark. By adopting the NVF and proposing the IF to assign weights to every embedding location and watermark pixel, respectively, we build the specific method CaDEED-N&I. In the experiments, we select the optimal parameters for NVF and IF via extensive experiments. In both the numerical and visual comparisons, the experimental results demonstrate the superiority of our proposed work.

Watermark Embedding for Multiscale Error Diffused Halftone Images by Adopting Visual Cryptography

Error Diffusion has been widely adopted in the printing industry due to its good visual quality and simple implementation. However, error diffusion still possesses its own deficiencies. Thus multiscale error diffusion (MED) has been developed, and this method outperforms traditional error diffusion according to extensive research results. The majority of previous halftone image watermarking techniques cannot be directly applied to MED halftone images. Since there is no halftone visual watermarking (HVW) method for MED halftone images in existing methods, we propose the first HVW method for MED halftone images, Copyright Protecting Multiscale Error Diffusion (CoP-MED), in this paper. By adopting the visual cryptography principle, CoP-MED can effectively embed a secret pattern into two MED halftone images, where the secret pattern can be decoded clearly by simply overlaying the two stego halftone images or performing not-exclusive-or operation between them. Parameter selection is also discussed based on the experimental results. Later, in comparison tests, CoP-MED shows superior performance compared to existing works.

Clustered-Dot Screen Design for Digital Multitoning

Digital multitoning is an extension of halftoning for rendering more than two tones at each pixel for higher image quality. Although a lot of effort has been put in generating dispersed dots previously, the blue-noise feature can hardly be achieved for those printers utilizing the electrophotography (EP) process to avoid the physically unstable isolated dots. To overcome this issue, Chandu et al. proposed a screening method for yielding green-noise dot clusters, yet noisy multitone texture was accompanied. This degrades the visual quality and the stability of tone rendering. In this paper, a significantly improved homogeneity of clustered dots can be achieved by the proposed screening method based upon the new inter-iterative clustered-dot direct multi-bit search algorithm. Compared with the former approaches, the inter-iteration design leads to less error by the updated initial multitone patterns. As demonstrated in the experimental results, both of the high homogenous multitone texture and less noisy perception at all absorptance levels are offered in contrast to the former Chandu et al.'s results. The high-quality output proves it as a very competitive candidate for EP printers, e.g., laser printers.

Dot-Diffused Halftoning With Improved Homogeneity

Compared with the error diffusion, dot diffusion provides an additional pixel-level parallelism for digital halftoning. However, even though its periodic and blocking artifacts had been eased by the previous works, it was still far from satisfactory in terms of the blue noise spectrum perspective. In this paper, we strengthen the relation among the pixel locations of the same processing order by an iterative halftoning method, and the results demonstrate a significant improvement. Moreover, a new approach of deriving the averaged power spectrum density is proposed to avoid the regular sampling of the well-known Bartlett's procedure which inaccurately presents the halftone periodicity of certain halftoning techniques with parallelism. As a result, the proposed dot diffusion is substantially superior to the state-of-the-art parallel halftoning methods in terms of visual quality and artifact-free property, and competitive runtime to the theoretical fastest ordered dithering is offered simultaneously.

Theoretical Bounds of Direct Binary Search Halftoning

Direct binary search (DBS) produces the images of the best quality among half-toning algorithms. The reason is that it minimizes the total squared perceived error instead of using heuristic approaches. The search for the optimal solution involves two operations: (1) toggle and (2) swap. Both operations try to find the binary states for each pixel to minimize the total squared perceived error. This error energy minimization leads to a conjecture that the absolute value of the filtered error after DBS converges is bounded by half of the peak value of the autocorrelation filter. However, a proof of the bound's existence has not yet been found. In this paper, we present a proof that shows the bound existed as conjectured under the condition that at least one swap occurs after toggle converges. The theoretical analysis also indicates that a swap with a pixel further away from the center of the autocorrelation filter results in a tighter bound. Therefore, we propose a new DBS algorithm which considers toggle and swap separately, and the swap operations are considered in the order from the edge to the center of the filter. Experimental results show that the new algorithm is more efficient than the previous algorithm and can produce half-toned images of the same quality as the previous algorithm.

Progressive halftone watermarking using multilayer table lookup strategy

In this paper, a halftoning-based multilayer watermarking of low computational complexity is proposed. An additional data-hiding technique is also employed to embed multiple watermarks into the watermark to be embedded to improve the security and embedding capacity. At the encoder, the efficient direct binary search method is employed to generate 256 reference tables to ensure the output is in halftone format. Subsequently, watermarks are embedded by a set of optimized compressed tables with various textural angles for table lookup. At the decoder, the least mean square metric is considered to increase the differences among those generated phenotypes of the embedding angles and reduce the required number of dimensions for each angle. Finally, the naïve Bayes classifier is employed to collect the possibilities of multilayer information for classifying the associated angles to extract the embedded watermarks. These decoded watermarks can be further overlapped for retrieving the additional hidden-layer watermarks. Experimental results show that the proposed method requires only 8.4 ms for embedding a watermark into an image of size 512×512 , under the 32-bit Windows 7 platform running on 4GB RAM, Intel core i7 Sandy Bridge with 4GB RAM and IDE Visual Studio 2010. Finally, only 2 MB is required to store the proposed compressed reference table.

Efficient halftoning based on multiple look-up tables

Look-up table (LUT) halftoning is an efficient way to construct halftone images and approximately simulate the dot distribution of the learned halftone image set. In this paper, a general mechanism named multiple look-up table (MLUT) halftoning is proposed to generate the halftones of direct binary search (DBS), whereas the high efficient characteristic of the LUT is still preserved. In the MLUT, the standard deviation is adopted as an important feature to classify various tables. In addition, the proposed quick standard deviation evaluation is employed to yield an extremely low computational complexity in calculating the standard deviation. In the parameter optimization, the autocorrelation is adopted because it can fully characterize the periodicity of dot distribution. Experimental results demonstrate that the dot distribution generated by the proposed method approximates to that of the DBS, which enables the proposed scheme as a very competitive candidate in the copying and printing industry.

Oriented modulation for watermarking in direct binary search halftone images

In this paper, a halftoning-based watermarking method is presented. This method enables high pixel-depth watermark embedding, while maintaining high image quality. This technique is capable of embedding watermarks with pixel depths up to 3 bits without causing prominent degradation to the image quality. To achieve high image quality, the parallel oriented high-efficient direct binary search (DBS) halftoning is selected to be integrated with the proposed orientation modulation (OM) method. The OM method utilizes different halftone texture orientations to carry different watermark data. In the decoder, the least-mean-square-trained filters are applied for feature extraction from watermarked images in the frequency domain, and the naïve Bayes classifier is used to analyze the extracted features and ultimately to decode the watermark data. Experimental results show that the DBS-based OM encoding method maintains a high degree of image quality and realizes the processing efficiency and robustness to be adapted in printing applications.

Alleviating dirty-window effect in medium frame-rate binary video halftones

A video display device having a lower number of bits per pixel than that required by the video to be displayed quantizes the video prior to its display. Halftoning can perform this quantization while attempting to reduce the visibility of certain quantization artifacts. Quantization artifacts are, nevertheless, not eliminated. A temporal artifact known as dirty-window effect (DWE) can be commonly observed in medium frame-rate binary video halftones. In this paper, we propose video halftone enhancement algorithms to reduce DWE. We assess the performance of the proposed algorithms by presenting objective measures for DWE in the original and the improved halftone videos. The expected contributions of this paper include three medium frame-rate binary video halftone enhancement algorithms that do the following: 1) reduce DWE under a spatial quality constraint; 2) reduce DWE under a spatial quality constraint with reduced complexity; and 3) reduce DWE under spatial and temporal quality constraints.

Characterization of electrophotographic print artifacts: banding, jitter, and ghosting

Electrophotographic (EP) print banding, jitter, and ghosting artifacts are common sources of print quality degradation. Traditionally, the characterization of banding and jitter artifacts relies mainly on the assumption that the defect has either a horizontal or vertical orientation which permits the simple 1-D analysis of the defect profile. However, this assumption can easily be violated if a small amount of printer or scanner skew is introduced to the analyzed images. In some cases, the defect can inherently be neither vertical nor horizontal. In this case, unless the defect orientation has been accurately detected before analysis, the 1-D-based approaches could bias the estimation of the defect severity. In this paper, we present an approach to characterize the jitter and banding artifacts of unrestricted orientation using wavelet filtering and 2-D spectral analysis. We also present a new system for detecting and quantifying ghosting defects. It includes a design for a printed test pattern to emphasize the ghosting defect and facilitate further processing and analysis. Wavelet filtering and a template matching technique are used to detect the ghost location along and across the scanned test pattern. A new metric is developed to quantify ghosting based upon its contrast, shape, and location consistency. Our experimental results show that the proposed approaches provide objective measures that quantify EP defects with a rank ordering correlation coefficient of 0.8 to 0.98, as compared to the subjective assessment of print quality experts.

Color extended visual cryptography using error diffusion

Color visual cryptography (VC) encrypts a color secret message into n color halftone image shares. Previous methods in the literature show good results for black and white or gray scale VC schemes, however, they are not sufficient to be applied directly to color shares due to different color structures. Some methods for color visual cryptography are not satisfactory in terms of producing either meaningless shares or meaningful shares with low visual quality, leading to suspicion of encryption. This paper introduces the concept of visual information pixel (VIP) synchronization and error diffusion to attain a color visual cryptography encryption method that produces meaningful color shares with high visual quality. VIP synchronization retains the positions of pixels carrying visual information of original images throughout the color channels and error diffusion generates shares pleasant to human eyes. Comparisons with previous approaches show the superior performance of the new method.

Hierarchical colorant-based direct binary search halftoning

Colorant-based direct binary search (CB-DBS) halftoning proposed in provides an image quality benchmark for dispersed-dot halftoning algorithms. The objective of this paper is to further push the image quality limit. An algorithm called hierarchical colorant-based direct binary search (HCB-DBS) is developed in this paper. By appropriately integrating yellow colorant into dot-overlapping and dot-positioning controls, it is demonstrated that HCB-DBS can achieve better halftone texture of both individual and joint dot-color planes, without compromising the dot distribution of more visible halftone of cyan and magenta colorants. The input color specification is first converted from colorant space to dot-color space with minimum brightness variation principle for full dot-overlapping control. The dot-colors are then split into groups based upon dot visibility. Hierarchical monochrome DBS halftoning is applied to make dot-positioning decision for each group, constrained on the already generated halftone of the groups with higher priority. And dot-coloring is decided recursively with joint monochrome DBS halftoning constrained on the related total dot distribution. Experiments show HCB-DBS improves halftone texture for both individual and joint dot-color planes. And it reduces the halftone graininess and free of color mottle artifacts, comparing to CB-DBS.

The hybrid screen--improving the breed

The hybrid screen is a halftoning method that generates stochastic dispersed dot textures in highlights and periodic clustered dot textures in midtones. Each tone level is sequentially designed from highlight to midtone by applying an iterative halftoning algorithm such as direct binary search (DBS). By allowing random seeding followed by swap-only DBS in a predefined core region within each microcell, each level can be designed while satisfying the stacking constraint and guaranteeing a smooth transition between levels. This paper describes a complete design process for the hybrid screen, introduces a number of enhancements to the original hybrid screen, and evaluates their impact on print quality. These enhancements include a multilevel screen design based on either extending a bilevel screen or directly generating a multilevel screen on a high resolution grid, and extending the hybrid screen design procedure to color by jointly optimizing the color screens using color DBS. For the multilevel screen, we show that the best choice for the core size critically depends on the bit depth and screen frequency. For the color hybrid screen, we demonstrate a significant improvement in the highlights over halftones generated by independently designed screens.

New spatial measure for dispersed-dot halftoning assuring good point distribution in any density

As a core component of dispersed-dot halftoning, this paper focuses on the definition of new measures for giving or measuring good point distributions in a plane. By defining good point distributions from a purely geometric viewpoint of circle packing, it is shown that the energy defined by a certain strong convex function satisfies the necessary conditions for obtaining good point distributions in any point density by minimizing the energy. The energy with such the conditions are mathematically plain and there are no obscure parameters. The theory is also significantly motivated by a requirement of the adjustability to discrete spaces, and it is shown that the conditions actually work well also in the spaces. As an application, by using technically simple methods, dispersed-dot halftone masks are designed and goodness of point distributions of masks are estimated.

Design of tone-dependent color-error diffusion halftoning systems

Grayscale error diffusion introduces nonlinear distortion (directional artifacts and false textures), linear distortion (sharpening), and additive noise. Tone-dependent error diffusion (TDED) reduces these artifacts by controlling the diffusion of quantization errors based on the input graylevel. We present an extension of TDED to color. In color-error diffusion, which color to render becomes a major concern in addition to finding optimal dot patterns. We propose a visually meaningful scheme to train input-level (or tone-) dependent color-error filters. Our design approach employs a Neugebauer printer model and a color human visual system model that takes into account spatial considerations in color reproduction. The resulting halftones overcome several traditional error-diffusion artifacts and achieve significantly greater accuracy in color rendition.

A new framework for characterization of halftone textures

Characterization of halftone texture is important for quantitative assessment of halftone quality. In this paper, we develop a new framework based on directional local sequency analysis and a filter bank structure. We decompose a halftone image into subband images, from which we can easily reconstruct the original halftone. Based on these subband images, we define the directional sequency spectrum which is analogous to the two-dimensional Fourier spectrum, and formulate several texture measures. Two test image sets are used to justify these measures.

Model-based color halftoning using direct binary search

In this paper, we develop a model-based color halftoning method using the direct binary search (DBS) algorithm. Our method strives to minimize the perceived error between the continuous tone original color image and the color halftone image. We exploit the differences in how the human viewers respond to luminance and chrominance information and use the total squared error in a luminance/chrominance based space as our metric. Starting with an initial halftone, we minimize this error metric using the DBS algorithm. Our method also incorporates a measurement based color printer dot interaction model to prevent the artifacts due to dot overlap and to improve color texture quality. We calibrate our halftoning algorithm to ensure accurate colorant distributions in resulting halftones. We present the color halftones which demonstrate the efficacy of our method.

Halftoning via direct binary search using analytical and stochastic printer models

We incorporate models for printer dot interactions within the iterative direct binary search (DBS) halftoning algorithm. Monochrome electro-photographic printers are considered. Both analytical and stochastic models are studied. In the analytical model it is assumed that the printer can generate a circular spot with constant absorptance at each printer addressable location, whereas the stochastic model is based on microscopic absorptance and variance measurements. We also present an efficient strategy for evaluating the change in computational cost as the search progresses. With our scheme, updating the change in error only involves a few fetches from two look-up-tables and some scalar multiplications and additions. Experimental results are provided that show that DBS with an appropriate model for printer dot interactions yields enhanced detail rendition, and improved tonal gradation in shadow areas.