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 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.     

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...     

Data hiding watermarking for halftone images

In many printer and publishing applications, it is desirable to embed data in halftone images. We proposed some novel data hiding methods for halftone images. For the situation in which only the halftone image is available, we propose data hiding smart pair toggling (DHSPT) to hide data by forced complementary toggling at pseudo-random locations within a halftone image. The complementary pixels are chosen to minimize the chance of forming visually undesirable clusters. Our experimental results suggest that DHSPT can hide a large amount of hidden data while maintaining good visual quality. For the situation in which the original multitone image is available and the halftoning method is error diffusion, we propose the modified data hiding error diffusion (MDHED) that integrates the data hiding operation into the error diffusion process. In MDHED, the error due to the data hiding is diffused effectively to both past and future pixels. Our experimental results suggest that MDHED can give better visual quality than DHSPT. Both DHSPT and MDHED are computationally inexpensive.     

具有掩盖图像的（2，2）可视密码方案

为解决传统可视密码像素膨胀及分存图像无意义等问题,文中提出了一个具有掩盖图像的（2,2）可视密码方案。方案中密图为黑白反色图像,利用半色调技术将两个灰度图像处理后的半色调图像作为掩盖图像,根据密图修改掩盖图像生成分存图像,叠加分存图像恢复密图。方案符合可视密码解密简单的特性且分存图像有意义,没有引入任何像素膨胀。     

Halftone visual cryptography.

Visual cryptography encodes a secret binary image (SI) into n shares of random binary patterns. If the shares are xeroxed onto transparencies, the secret image can be visually decoded by superimposing a qualified subset of transparencies, but no secret information can be obtained from the superposition of a forbidden subset. The binary patterns of the n shares, however, have no visual meaning and hinder the objectives of visual cryptography. Extended visual cryptography [1] was proposed recently to construct meaningful binary images as shares using hypergraph colourings, but the visual quality is poor. In this paper, a novel technique named halftone visual cryptography is proposed to achieve visual cryptography via halftoning. Based on the blue-noise dithering principles, the proposed method utilizes the void and cluster algorithm [2] to encode a secret binary image into n halftone shares (images) carrying significant visual information. The simulation shows that the visual quality of the obtained halftone shares are observably better than that attained by any available visual cryptography method known to date.     

On the use of context-weighting in lossless bilevel image compression.

We present a context-weighting algorithm that adaptively weights in real-time three-context models based on their relative accuracy. It can automatically select the better model over different regions of an image, producing better probability estimates than using either one of these models exclusively. Combined with the previously proposed block arithmetic coder for image compression (BACIC), the overall performance is slightly better than JBIG for the eight CCITT business-type test images, outperforms JBIG by 13.8% on halftone images, and by 17.5% for compounded images containing both text and halftones. Furthermore, users no longer need to select models as in JBIG and BACIC to get the better performance.     

High-capacity data hiding in halftone images using minimal-error bit searching and least-mean square filter.

In this paper, a high-capacity data hiding is proposed for embedding a large amount of information into halftone images. The embedded watermark can be distributed into several error-diffused images with the proposed minimal-error bit-searching technique (MEBS). The method can also be generalized to self-decoding mode with dot diffusion or color halftone images. From the experiments, the embedded capacity from 33% up to 50% and good quality results are achieved. Furthermore, the proposed MEBS method is also extended for robust watermarking against the degradation from printing-and-scanning and several kinds of distortions. Finally, a least-mean square-based halftoning is developed to produce an edge-enhanced halftone image, and the technique also cooperates with MEBS for all the applications described above, including high-capacity data hiding with secret sharing or self-decoding mode, as well as robust watermarking. The results prove much sharper than the error diffusion or dot diffusion methods.     

A multiscale error diffusion technique for digital halftoning

A new digital halftoning technique based on multiscale error diffusion is examined. We use an image quadtree to represent the difference image between the input gray-level image and the output halftone image. In iterative algorithm is developed that searches the brightest region of a given image via "maximum intensity guidance" for assigning dots and diffuses the quantization error noncausally at each iteration. To measure the quality of halftone images, we adopt a new criterion based on hierarchical intensity distribution. The proposed method provides very good results both visually and in terms of the hierarchical intensity quality measure.     

A feature-based digital watermarking scheme for halftone image

It is a challenging work to design a robust halftone image watermarking scheme against desynchronization attacks. In this paper, we propose a feature-based digital watermarking method for halftone images with low computational complexity, good visual quality and reasonable resistance toward desynchronization attacks. Firstly, the feature points are extracted from host halftone image by using multi-scale Harris–Laplace detector, and the local feature regions (LFRs) are constructed according to the feature scale theory. Secondly, discrete Fourier transform (DFT) is performed on the LFRs, and the embedding positions (DFT coefficients) are selected adaptively according to the magnitude spectrum information. Finally, the digital watermark is embedded into the LFRs by quantizing the magnitudes of the selected DFT coefficients. By binding the watermark with the geometrically invariant halftone image features, the watermark detection can be done without synchronization error. Simulation results show that the proposed scheme is invisible and robust against common signals processing such as median filtering, sharpening, noise adding, and JPEG compression, etc., and desynchronization attacks such as rotation, scaling, translation (RST), cropping, local random bend, and print-scan, etc.     

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.     

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.     

Adaptive-Hierarchical-Filtering Technique for High-Quality Magazine Image Reproduction

This paper proposes a novel adaptive filtering technique to achieve high-quality image enhancement when the image possesses the artifact of moiré pattern during the reproduction by different computer peripherals such as color copiers, or scanners plus printers.Commercial magazine images are halftoned images. Unacceptable noises and moiré distortion may occur when halftone images are copied (i.e., scanned and printed). In this paper, we analyze the formation of moiré patterns in both the frequency and spatial domain. Basically moiré noise often appears due to the aliased frequency when a halftone image is scanned. Based on the analysis of the scanned halftone image, we develop an adaptive filter to suppress the moiré artifacts and produce the high-quality image reproduction. The adaptive filter consists of modules of anti-aliased filter and image enhance filter: the anti-aliased filter is applied to cancel aliased low frequency components (moiré distortion); the image enhance filter is applied to sharpen image edges. It depends on the information provided by an image classification module to decide either the anti-aliased or image enhance module should be applied. The classification module is developed based on a set of pyramid images to determine an edge is either a global true edge (for sharpening enhancement) or a local halftones micro-structural edge (for moiré reduction). Depending on the information from the classification module, the adaptive filter technique then applies the anti-aliased filter to the halftone micro-structured edge or the enhanced filter to the image global edge correctly and efficiently, and therefore both the moiré reduction and image enhancement can be achieved simultaneously. Experimental results show the outstanding effectiveness of the presented technique for high-quality magazine image reproduction.Joseph Shu was born in Taiwan, Republic of China in 1954. He received his B.S. degree from Communication Engineering department, National Chiao-Tung University, Taiwan, R.O.C. in 1978, M.S. degree in 1984 and Ph.D. degree in 1986 both in Electric, Computer, and Systems Engineering department, Rensselaer Polytechnic Institute, Troy, New York. From 1986 to 1990, Dr. Shu worked for NYNEX Corporation. From 1990 to 1991, he worked in Hewlett-Packard Labs. Since 1991, he has been working for Epson. He is now a consultant scientist for Epson Palo Alto Lab. He has 35 U.S. patents. He has published over 25 technical papers in image segmentation, enhancement, restoration, analysis, moire reduction, pattern recognition, color processing and halftoning.Tsung-Nan Lin received B.S. degree in electrical engineering from National Taiwan University, Taiwan, R.O.C. in 1989, and M.A. and Ph.D. degrees from Princeton University in 1993 and 1996, respectively, both in electrical engineering department. He was a Teaching Assistant with the Department of Electrical Engineering from 1991 to 1992. Hewas with NEC Research Institute as a Research Assistant from 1992 to 1996. He has been with EPSON R&D Inc and EMC. Since Feb. 2002, he has been with Department of Electrical Engineering and Graduate Institute of Communication Engineering, National Taiwan University, Taipei, Taiwan. Tsung-Nan Lin is a member of PHI TAUPHI scholastic honor society and a senior member of IEEE.     

Tree-structured method for LUT inverse halftoning and for imagehalftoning

The authors previously proposed a look up table (LUT) based method 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. Many of the entries in the LUT are unused because the corresponding binary patterns hardly occur in commonly encountered halftones. These are called nonexistent patterns. In this paper, we propose a tree structure which will reduce the storage requirements of an LUT by avoiding nonexistent patterns. We demonstrate the performance on error diffused images and ordered dither images. Then, we introduce LUT based halftoning and tree-structured LUT (TLUT) halftoning. Even though the TLUT method is more complex than LUT halftoning, it produces better halftones and requires much less storage than LUT halftoning. We demonstrate how the error diffusion characteristics can be achieved with this method. Afterwards, our algorithm is trained on halftones obtained by direct binary search (DBS). The complexity of TLUT halftoning is higher than the error diffusion algorithm but much lower than the DBS algorithm. Also, the halftone quality of TLUT halftoning increases if the size of the TLUT gets bigger. Thus, the halftone image quality between error diffusion and DBS will be achieved depending on the size of the tree-structure in the TLUT algorithm     

Self-conjugate watermarking technique for halftone images

A novel method for hiding visual patterns in a single error diffused halftone image is presented called self-conjugate error diffusion (SCED). The hidden patterns appear on the halftone image when the halftone image is folded or is overlapped with its own rotated version. Simulation results show that the halftone images have good visual quality and the hidden pattern is clearly visible.     

Nonlinear filtering of statistically connected video sequences based on hidden Markov chains

A method for the synthesis of algorithms for nonlinear filtering of statistically connected (correlated) video sequences of digital halftone images distorted by a white Gaussian noise is proposed. The method is based on the use of hidden Markov chains as a mathematical model for video sequences of digital halftone images, which, in limited observation intervals, can be represented by multidimensional Markov chains.     

Robust Watermarking with Kernels-Alternated Error Diffusion and Weighted Lookup Table in Halftone Images

A halftone watermarking method of high quality, robustness, and capacity flexibility is presented in this paper. An objective halftone image quality evaluation method based on the human visual system obtained by a least-mean-square algorithm is also introduced. In the encoder, the kernels-alternated error diffusion (KAEDF) is applied. It is able to maintain the computational complexity at the same level as ordinary error diffusion. Compared with Hel-Or using ordered dithering, the proposed KAEDF yields a better image quality through using error diffusion. We also propose a weighted lookup table (WLUT) in the decoder instead of lookup table (LUT), as proposed by Pei and Guo, so as to achieve a higher decoded rate. As the experimental results demonstrate, this technique is able to guard against degradation due to tampering, cropping, rotation, and print-and-scan processes in error-diffused halftone images.     

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.     

Hiding color watermarks in halftone images using maximum-similarity binary patterns

This paper presents a halftoning-based watermarking method that enables the embedding of a color image into binary black-and-white images. To maintain the quality of halftone images, the method maps watermarks to halftone channels using homogeneous dot patterns. These patterns use a different binary texture arrangement to embed the watermark. To prevent a degradation of the host image, a maximization problem is solved to reduce the associated noise. The objective function of this maximization problem is the binary similarity measure between the original binary halftone and a set of randomly generated patterns. This optimization problem needs to be solved for each dot pattern, resulting in processing overhead and a long running time. To overcome this restriction, parallel computing techniques are used to decrease the processing time. More specifically, the method is tested using a CUDA-based parallel implementation, running on GPUs. The proposed technique produces results with high visual quality and acceptable processing time.     

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.