Model-based digital halftoning

Digital halftoning is the process of generating a pattern of pixels with a limited number of colors that, when seen by the human eye, is perceived as a continuous-tone image. Digital halftoning is used to display continuous-tone images in media in which the direct rendition of the tones is impossible. The most common example of such media is ink or toner on paper, and the most common rendering devices for such media are, of course, printers. Halftoning works because the eye acts as a spatial low-pass filter that blurs the rendered pixel pattern, so that it is perceived as a continuous-tone image. Although all halftoning methods rely at least implicitly, on some understanding of the properties of human vision and the display device, the goal of model-based halftoning techniques is to exploit explicit models of the display device and the human visual system (HVS) to maximize the quality of the displayed images. Based on the type of computation involved, halftoning algorithms can be broadly classified into three categories: point algorithms (screening or dithering), neighborhood algorithms (error diffusion), and iterative algorithms [least squares and direct binary search (DBS)]. All of these algorithms can incorporate HVS and printer models. The best halftone reproductions, however, are obtained by iterative techniques that minimize the (squared) error between the output of the cascade of the printer and visual models in response to the halftone image and the output of the visual model in response to the original continuous-tone image.     

An adaptive inverse halftoning algorithm

A class of inverse halftoning algorithms that recovers grayscale (continuous-tone) images from halftone images is proposed. The basic structure is an optimized linear filter. Then, a properly designed adaptive postprocessor is employed to enhance the recovered image quality. Finally, a multistage space-varying algorithm is developed that uses the basic linear filter structure as before but with spatially adaptive parameters.     

A dual interpretation for direct binary search and its implicationsfor tone reproduction and texture quality

The direct binary search (DBS) algorithm employs a search heuristic to minimize the mean-squared perceptually filtered error between the halftone and continuous-tone original images. Based on an efficient method for evaluating the effect on the mean squared error of trial changes to the halftone image, we show that DBS also minimizes in a pointwise sense the absolute error under the same visual model, but at twice the viewing distance associated with the mean-squared error metric. This dual interpretation sheds light on the convergence properties of the algorithm, and clearly explains the tone bias that has long been observed with halftoning algorithms of this type. It also demonstrates how tone bias and texture quality are linked via the scale parameter, the product of printer resolution and viewing distance. Finally, we show how the tone bias can be eliminated by tone-correcting the continuous-tone image prior to halftoning it.     

Joint halftoning and watermarking

A framework to jointly halftone and watermark a grayscale images is presented. The framework needs the definition of three components: a human visual system (HVS)-based error metric between the continuous-tone image and a halftone, a watermarking scheme with a corresponding watermark detection measure, and a search strategy to traverse the space of halftones. We employ the HVS-based error metric used in the direct binary search (DBS) halftoning algorithm, and we use a block-based spread spectrum watermarking scheme and the toggle and swap search strategy of DBS. The halftone is printed on a desktop printer and scanned using a flatbed scanner. The watermark is detected from the scanned image and a number of post-processed versions of the scanned image, including one restored in Adobe PhotoShop. The results show that the watermark is extremely resilient to printing, scanning, and post-processing; for a given baseline image quality, joint optimization is better than watermarking and halftoning independently. For this particular algorithm, the original continuous-tone image is required to detect the watermark.     

Inverse halftoning via MAP estimation

There has been a tremendous amount of research in the area of image halftoning, where the goal has been to find the most visually accurate representation given a limited palette of gray levels (often just two, black and white). This paper focuses on the inverse problem, that of finding efficient techniques for reconstructing high-quality continuous-tone images from their halftoned versions. The proposed algorithms are based on a maximum a posteriori (MAP) estimation criteria using a Markov random field (MRF) model for the prior image distribution. Image estimates obtained with the proposed model accurately reconstruct both the smooth regions of the image and the discontinuities along image edges. Algorithms are developed and example gray-level reconstructions are presented generated from both dithered and error-diffused halftone originals. Application of the technique to the problems of rescreening and the processing of halftone images are shown.     

Digital color halftoning with generalized error diffusion andmultichannel green-noise masks

In this paper, we introduce two novel techniques for digital color halftoning with green-noise-stochastic dither patterns generated by homogeneously distributing minority pixel clusters. The first technique employs error diffusion with output-dependent feedback where, unlike monochrome image halftoning, an interference term is added such that the overlapping of pixels of different colors can be regulated for increased color control. The second technique uses a green-noise mask, a dither array designed to create green-noise halftone patterns, which has been constructed to also regulate the overlapping of different colored pixels. As is the case with monochrome image halftoning, both techniques are tunable, allowing for large clusters in printers with high dot-gain characteristics, and small clusters in printers with low dot-gain characteristics.     

基于离散Sibson插值的反半色调算法

本文提出了一种基于离散Sibson插值的盲反半色调方法.算法建立在统一的离散Voronoi图框架之上,通过自适应Voronoi区域估计得到种子点的灰度值,然后通过离散Sibson插值将传统的反半色调问题转化为插值问题并计算获取连续色调图像.算法不需要知道任何先验知识,因此算法具有更广的适用性,可以被应用于任意方法生成的...     

Inverse halftoning algorithm using edge-based lookup table approach

The inverse halftoning algorithm is used to reconstruct a gray image from an input halftone image. Based on the recently published lookup table (LUT) technique, this paper presents a novel edge-based LUT method for inverse halftoning which improves the quality of the reconstructed gray image. The proposed method first uses the LUT-based inverse halftoning method as a preprocessing step to transform the given halftone image to a base gray image, and then the edges are extracted and classified from the base gray image. According to these classified edges, a novel edge-based LUT is built up to reconstruct the gray image. Based on a set of 30 real training images with both low- and high-frequency contents, experimental results demonstrated that the proposed method achieves a better image quality when compared to the currently published two methods, by Chang et al. and Mes$80e and Vaidyanathan.     

A new class of B/W halftoning algorithms

A new class of dithering algorithms for black and white (B/W) images is presented. The basic idea behind the technique is to divide the image into small blocks and minimize the distortion between the original continuous-tone image and its low-pass-filtered halftone. This corresponds to a quadratic programming problem with linear constraints, which is solved via standard optimization techniques. Examples of B/W halftone images obtained by this technique are compared to halftones obtained via existing dithering algorithms.     

连续图像数字半调处理及性能分析

本文阐述了连续图像数字半调处理的基本理论,包括有序抖动数字半调处理、误差扩散数字半调处理,并对2种处理进行了性能分析。     

Adaptive threshold modulation for error diffusion halftoning

Grayscale digital image halftoning quantizes each pixel to one bit. In error diffusion halftoning, the quantization error at each pixel is filtered and fed back to the input in order to diffuse the quantization error among the neighboring grayscale pixels. Error diffusion introduces nonlinear distortion (directional artifacts), linear distortion (sharpening), and additive noise. Threshold modulation, which alters the quantizer input, has been previously used to reduce either directional artifacts or linear distortion. This paper presents an adaptive threshold modulation framework to improve halftone quality by optimizing error diffusion parameters in the least squares sense. The framework models the quantizer implicitly, so a wide variety of quantizers may be used. Based on the framework, we derive adaptive algorithms to optimize 1) edge enhancement halftoning and 2) green noise halftoning. In edge enhancement halftoning, we minimize linear distortion by controlling the sharpening control parameter. We may also break up directional artifacts by replacing the thresholding quantizer with a deterministic bit flipping (DBF) quantizer. For green noise halftoning, we optimize the hysteresis coefficients.     

Stochastic Screen Halftoning for Electronic Imaging Devices

For numerous digital imaging applications, there is a need to maintain the highest quality perceived image, while utilizing a printer or display that can only achieve a limited number of output states. Digital halftoning is the approach that has been widely used to meet this demand. In this focus paper, we provide a short summary of halftone techniques, then we concentrate on the newer and expanding roles of stochastic halftone screens—which are free of regular periodic structures and have numerous advantages in quality color rendering. We address some theoretical issues, design and optimality issues, printer compensation issues, and color quality issues that pertain to the development and use of stochastic screens for electronic imaging devices.     

Look-up table (LUT) method for inverse halftoning

In this paper we propose look-up table (LUT) based methods for inverse halftoning of images. The LUT for inverse halftoning is obtained from the histogram gathered from a few sample halftone images and corresponding original images. The method is extremely fast (no filtering is required) and the PSNR and visual image quality achieved is comparable to the best methods known for inverse halftoning. The LUT inverse halftoning method does not depend on the specific properties of the halftoning method, and can be applied to any halftoning method. Then, an algorithm for template selection for LUT inverse halftoning is introduced. We demonstrate the performance of the LUT inverse halftoning algorithm on error diffused images and ordered dithered images. We also extend LUT inverse halftoning to color halftones.     

A fast, high-quality inverse halftoning algorithm for errordiffused halftones

Halftones and other binary images are difficult to process with causing several degradation. Degradation is greatly reduced if the halftone is inverse halftoned (converted to grayscale) before scaling, sharpening, rotating, or other processing. For error diffused halftones, we present (1) a fast inverse halftoning algorithm and (2) a new multiscale gradient estimator. The inverse halftoning algorithm is based on anisotropic diffusion. It uses the new multiscale gradient estimator to vary the tradeoff between spatial resolution and grayscale resolution at each pixel to obtain a sharp image with a low perceived noise level. Because the algorithm requires fewer than 300 arithmetic operations per pixel and processes 7x7 neighborhoods of halftone pixels, it is well suited for implementation in VLSI and embedded software. We compare the implementation cost, peak signal to noise ratio, and visual quality with other inverse halftoning algorithms.     

Adaptive error diffusion and its application in multiresolutionrendering

Error diffusion is a procedure for generating high quality bilevel images from continuous-tone images so that both the continuous and halftone images appear similar when observed from a distance. It is well known that certain objectionable patterning artifacts can occur in error-diffused images. Here, we consider a method for adjusting the error-diffusion filter concurrently with the error-diffusion process so that an error criterion is minimized. The minimization is performed using the least mean squares (LMS) algorithm in adaptive signal processing. Using both raster and serpentine scanning, we show that such an algorithm produces better halftone image quality compared to traditional error diffusion with a fixed filter. Based on the adaptive error-diffusion algorithm, we propose a method for constructing a halftone image that can be rendered at multiple resolutions. Specifically, the method generates a halftone from a continuous tone image such that if the halftone is down-sampled, a binary image would result that is also a high quality rendition of the continuous-tone image at a reduced resolution. Such a halftone image is suitable for progressive transmission, and for cases where rendition at several resolutions is required. Cases for noninteger scaling factors are also considered.     

Inverse halftoning using binary permutation filters

The problem of reconstructing a continuous-tone image given its ordered dithered halftone or its error-diffused halftone image is considered. We develop a modular class of nonlinear filters that can reconstruct the continuous-tone information preserving image details and edges that provide important visual cues. The proposed nonlinear reconstruction algorithms, denoted as binary permutation filters, are based on the space and rank orderings of the halftone samples provided by the multiset permutation of the "on" pixels in a halftone observation window. For a given window size, we obtain a wide range of filters by varying the amount of space-rank ordering information utilized in the estimate. For image reconstructions from ordered dithered halftones, we develop periodically space-varying filters that can account for the periodical nature of the underlying screening process. A class of suboptimal but simpler space-invariant reconstruction filters are also proposed and tested. Constrained LMS type algorithms are employed for the design of reconstruction filters that minimize the reconstruction mean squared error. We present simulations showing that binary permutation filters are modular, robust to image source characteristics, and that they produce high visual quality image reconstruction.     

自适应反馈视觉感知差的误差扩散半色调算法

文章基于人眼对亮度的视觉感受特性。提出了一种自适应反馈视觉感知差的误差扩散算法（PEF Error Diffusion算法）。首先提出视觉感知差的概念，然后根据原图像区域的灰度特征，自适应地计算反馈系数，将视觉感知差反馈给原连续调图像，以补偿误差扩散所引起的不同区域的灰度损失。实验结果表明，由于视觉感知差的引入及反馈系数的自适应变化。PEF Error Diffusion算法能够明显增强图像的整体对比度．减弱点增益现象的不良影响，并准确再现更多的图像细节．因而表现出比传统算法更好的主观视觉效果。     

Binary grayscale halftone pattern generation using binary artificial bee colony (bABC)

In grayscale context, digital halftoning can be considered as binary pattern generation task where 0- and 1-valued pixels represent black and white, respectively. This paper presents application of artificial bee colony (ABC) in its modified binary form called binary ABC (bABC) toward generation of optimized binary halftone patterns. The human visual system incorporated cost function formulation addresses the tonal and structural parity between the original and halftone images along with pleasant halftone appearance. A pattern look-up table (p-LUT) approach is investigated including edge enhancement in halftone images. The results are presented pictorially and evaluated objectively. Comparison between the presented method and established halftoning techniques is also drawn to judge the potential of the presented bABC generated p-LUT approach. The pictorial presentations as well as objective evaluation show that the presented method may be potentially useful in the field of digital halftoning.     

Algorithms of halftoning color images with edge enhancement

Printers usually generate a limited number of colors and lack the ability of producing continuous-tone color images. Traditional error-diffusion algorithms are used to solve this problem. Compared with other approaches, the approaches of using error-diffusion in general can generate halftoned images of better quality. However, smeared edges and textures may occur in these halftoned images. To produce halftoned images of higher quality, these artifacts due to unstable images, dot-overlap, and error-diffusion must be eliminated or reduced. In this paper, we show that unstable images can be eliminated or reduced through using a proper color difference formula to select the reproduction colors even vector error-diffusion is performed in the RGB domain. We also present a method of using different filters to halftone different components of a color. This approach may have clearer and sharper edges for halftoned color images. Unexpected colors may be generated due to dot-overlap in the printing process. We have presented a method to eliminate this color distortion in the process of error-diffusion. Halftoning a color image by our proposed error-diffusion algorithm with edge enhancement has the following characteristics: the unstable images do not exist; the color-error caused by dot-overlap is corrected; and the smeared edges are sharpened.     

Inkjet printer model-based halftoning.

The quality of halftone prints produced by inkjet (IJ) printers can be limited by random dot-placement errors. While a large literature addresses model-based halftoning for electrophotographic printers, little work has been done on model-based halftoning for IJ printers. In this paper, we propose model-based approaches to both iterative least-squares halftoning and tone-dependent error diffusion (TDED). The particular approach to iterative least-squares halftoning that we use is direct binary search (DBS). For DBS, we use a stochastic model for the equivalent gray-scale image, based on measured dot statistics of printed IJ halftone patterns. For TDED, we train the tone-dependent weights and thresholds to mimic the spectrum of halftone textures generated by model-based DBS. We do this under a metric that enforces both the correct radially averaged spectral profile and angular symmetry at each radial frequency. Experimental results generated with simulated printers and a real printer show that both IJ model-based DBS and IJ model-based TDED very effectively suppress IJ printer-induced artifacts.