Error Diffusion Halftoning Research Articles

Quality evaluation metric for greyscale error diffusion halftone images based on texture and visual characteristics

ABSTRACTHalftone images produced by error diffusion algorithms suffer from texture structures that decrease their visual qualities, such as worm-like and stripe-like defects. An effective quality evaluation metric is needed to evaluate various error diffusion halftoning algorithms and their corresponding halftone images. A texture distortion evaluation metric (TDEM) is proposed to measure the texture distortions within the referenced halftoned greyscale images. First, the weights of different tonal regions were assigned based on the two types of visual objects available and the locations of the texture structures. Then, based on image structure correlations and human visual characteristics, a block operation was performed and TDEM values were obtained by summing the local block-weighted variances based on image information. The proposed metric was validated using objective comparison and psycho-visual experiments. Results indicate that the metric can measure texture distortions effectively, and that the results are consistent with subjective visual perception.

Classification of Error-Diffused Halftone Images Based on Spectral Regression Kernel Discriminant Analysis

This paper proposes a novel algorithm to solve the challenging problem of classifying error-diffused halftone images. We firstly design the class feature matrices, after extracting the image patches according to their statistics characteristics, to classify the error-diffused halftone images. Then, the spectral regression kernel discriminant analysis is used for feature dimension reduction. The error-diffused halftone images are finally classified using an idea similar to the nearest centroids classifier. As demonstrated by the experimental results, our method is fast and can achieve a high classification accuracy rate with an added benefit of robustness in tackling noise.

Research on Pseudo-Contour of Halftone Images Based on Multi-level Error Diffusion Algorithm

To research the distribution characteristics of pseudo-contour in Multi-level Error Diffusion(MED) halftone images,based on the analysis of generation mechanism of MED,three images which were partial bright,normal and dark separtely,were processed by multi-level error diffusion halftoning algorithm with different quantization threshold values. The compared results showed that pseudo-contour related with the gradual level distribution of the images and quantization threshold values.On this basis,a new method was put forward to modulate the quantization threshold values in midtones where pseudo-contour appeared obviously.The calculating results showed that it is effective to eliminate the pseudo-contour in multi-level error diffusion halftone images.

Multi-Level Halftoning by IGS Quantization

Improved gray-scale (IGS) quantization is a known method for re-quantizing digital gray-scale images for data compression while producing halftones by adding a level of randomness to improve visual quality of the resultant images. In this paper, first, analyzing the IGS quantizing operations reveals the capability of conserving a DC signal level of a source image through the quantization. Then, a complete procedure for producing a multi-level halftone image by IGS quantization that can achieve the DC conservation is presented. Also, the procedure uses the scanning of source pixels in an order such that geometric patterns can be prevented from occurring in the resulting halftone image. Next, the performance of the multi-level IGS halftoning is evaluated by experiments conducted on 8-bit gray-scale test images in comparison with the halftoning by error diffusion. The experimental result demonstrates that a signal level to be quantized in the IGS halftoning varies more randomly than that in the error diffusion halftoning, but not entirely randomly. Also, visual quality of the resulting halftone images was measured by subjective evaluations of viewers. The result indicates that for 3 or more-bit, in other words, 8 or more-level halftones, the IGS halftoning achieves image quality comparable to that by the error diffusion.

Mixed compression algorithm for error-diffusion halftone image based on look-up table

Mixed compression algorithm for error-diffusion halftone image based on look-up table

Watermarking in halftone images with parity-matched error diffusion

In this paper, a halftone watermarking technique of high watermark rate, robustness, and watermark-rate flexibility is presented. This technique, namely the parity-matched error diffusion (PMEDF) method, is capable of achieving an embedded watermark rate as high as 6.25–25% with good image quality and without the need for the original image as the reference for the decoding. The proposed PMEDF method employs the high efficient parity-matching strategy to spread a watermark bit to each pixel of a block of the host image. Thus, the majority voting mechanism can be applied for decoding to achieve an advantage of high robustness. As documented in the experimental results, this technique is capable of guarding against degradation, due to cropping, tampering, as well as print-and-scan process in error-diffused halftone images.

Neural network based method for image halftoning and inverse halftoning

A hybrid neural network based method for halftoning and inverse halftoning of digital images is presented. The halftone image is performed by single-layer perceptron neural network (SLPNN), and its corresponding continuous-tone image is reconstructed by radial-basis function neural network (RBFNN). The combined training procedure produces halftone images and the corresponding continuous tone images at the same time. The PSNR performance and visual image quality of these contone images achieved is comparable to the well-known inverse halftoning methods. The resultant halftone images compared with the error diffusion halftone are visually good, too. Furthermore, we apply different kinds of halftone images to a bi-level image compression method, called Block Arithmetic Coding for Image Compression (BACIC), which is better than the current facsimile methods.

Training-Based Descreening

Conventional halftoning methods employed in electrophotographic printers tend to produce Moiré artifacts when used for printing images scanned from printed material, such as books and magazines. We present a novel approach for descreening color scanned documents aimed at providing an efficient solution to the Moiré problem in practical imaging devices, including copiers and multifunction printers. The algorithm works by combining two nonlinear image-processing techniques, resolution synthesis-based denoising (RSD), and modified smallest univalue segment assimilating nucleus (SUSAN) filtering. The RSD predictor is based on a stochastic image model whose parameters are optimized beforehand in a separate training procedure. Using the optimized parameters, RSD classifies the local window around the current pixel in the scanned image and applies filters optimized for the selected classes. The output of the RSD predictor is treated as a first-order estimate to the descreened image. The modified SUSAN filter uses the output of RSD for performing an edge-preserving smoothing on the raw scanned data and produces the final output of the descreening algorithm. Our method does not require any knowledge of the screening method, such as the screen frequency or dither matrix coefficients, that produced the printed original. The proposed scheme not only suppresses the Moiré artifacts, but, in addition, can be trained with intrinsic sharpening for deblurring scanned documents. Finally, once optimized for a periodic clustered-dot halftoning method, the same algorithm can be used to inverse halftone scanned images containing stochastic error diffusion halftone noise.

Hardcopy image barcodes via block-error diffusion

Error diffusion halftoning is a popular method of producing frequency modulated (FM) halftones for printing and display. FM halftoning fixes the dot size (e.g., to one pixel in conventional error diffusion) and varies the dot frequency according to the intensity of the original grayscale image. We generalize error diffusion to produce FM halftones with user-controlled dot size and shape by using block quantization and block filtering. As a key application, we show how block-error diffusion may be applied to embed information in hardcopy using dot shape modulation. We enable the encoding and subsequent decoding of information embedded in the hardcopy version of continuous-tone base images. The encoding-decoding process is modeled by robust data transmission through a noisy print-scan channel that is explicitly modeled. We refer to the encoded printed version as an image barcode due to its high information capacity that differentiates it from common hardcopy watermarks. The encoding/halftoning strategy is based on a modified version of block-error diffusion. Encoder stability, image quality versus information capacity tradeoffs, and decoding issues with and without explicit knowledge of the base image are discussed.

Hybrid pixel-based data hiding and block-based watermarking for error-diffused halftone images

A low computational complexity noise-balanced error diffusion (NBEDF) technique is proposed for embedding watermarks into error-diffused images. The visual decoding pattern can be perceived when two or more similar NBEDF images are overlaid, even in a high activity region. Also, with the modified improved version of NBEDF, two halftone images can be made from two totally different gray-tone images, and still provide a clear and sharp visual decoding pattern. With self-decoding techniques, we can also decode the pattern with only one NBEDF image. However, the NBEDF method is not so robust to damage due to printing or other distortions. Thus, a kernels-alternated error diffusion (KAEDF) technique is proposed. By using them alternately in the halftone process, we find that two well-known kernels (Jarvis, J.F. et al., 1976; Stucki, P., 1981) are compatible. In the decoder, because the spectral distributions of Jarvis and Stucki kernels are different in the 2D fast Fourier transform domain, we use the cumulative squared Euclidean distance criterion to determine each cell in a watermarked halftone image belonging to either Jarvis or Stucki, and then decode the watermark. Furthermore, because the detailed textures of Jarvis and Stucki patterns are somewhat different in the spatial domain, the lookup table (LUT) technique is also used for fast decoding. From simulation results, the correct decoding rates for both techniques are high and extremely robust, even after printing and scanning processes. Finally, we extend the hybrid NBEDF and KAEDF algorithms to two color EDF halftone images, where 8 independent KAEDF watermarks and 16 NBEDF watermarks can be inserted and still achieve a high-quality result.

Near-lossless/lossless compression of error-diffused images using a two-pass approach

The current international standard, the Joint Bilevel Image Experts Group (JBIG), is a representative of a bilevel image compression algorithm. It compresses bilevel images with high performance, but it shows relatively low performance in compressing error-diffused halftone images. This paper proposes a new bilevel image compression for error-diffused images, which is based on Bayes' theorem. The proposed coding procedure consists of two passes. It groups 2 x 2 dots into a cell, where each cell is represented by the number of black dots and the locations of the black dots in the cell. The number of black dots in the cell is encoded in the first pass, and their locations are encoded in the second pass. The first pass performs a near-lossless compression, which can be refined to be lossless by the second pass. Experimental results show a high compression performance for the proposed method when it is applied to error-diffused images.

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.

Design and analysis of vector color error diffusion halftoning systems

Traditional error diffusion halftoning is a high quality method for producing binary images from digital grayscale images. Error diffusion shapes the quantization noise power into the high frequency regions where the human eye is the least sensitive. Error diffusion may be extended to color images by using error filters with matrix-valued coefficients to take into account the correlation among color planes. For vector color error diffusion, we propose three contributions. First, we analyze vector color error diffusion based on a new matrix gain model for the quantizer, which linearizes vector error diffusion. The model predicts the key characteristics of color error diffusion, esp. image sharpening and noise shaping. The proposed model includes linear gain models for the quantizer by Ardalan and Paulos (1987) and by Kite et al. (1997) as special cases. Second, based on our model, we optimize the noise shaping behavior of color error diffusion by designing error filters that are optimum with respect to any given linear spatially-invariant model of the human visual system. Our approach allows the error filter to have matrix-valued coefficients and diffuse quantization error across color channels in an opponent color representation. Thus, the noise is shaped into frequency regions of reduced human color sensitivity. To obtain the optimal filter, we derive a matrix version of the Yule-Walker equations which we solve by using a gradient descent algorithm. Finally, we show that the vector error filter has a parallel implementation as a polyphase filterbank.

On the phase response of the error diffusion filter for image halftoning

Conventional error diffusion halftoning uses a causal error filter. We propose the iterative error diffusion algorithm by extending the error diffusion to accommodate noncausal error filters. We realize the importance of the phase response of the error filter in the error diffusion halftoning method, and demonstrate it using examples. Iterative error diffusion is able to realize a zero phase error filter. We also trace a drawback of error diffusion to the shape of the error filter, and provide a remedy. The results obtained using a zero phase error filter in the iterative error diffusion algorithm are, in our opinion, superior to the error diffusion halftones.

Does Error-Diffusion Halftone Texture Mask Banding?

One type of common printer banding artifact is a thin white horizontal line. This can result from a clogged ink jet nozzle, from paper-feed problems in electrophotographic printers, and from other causes. The halftone texture might be expected to mask the visibility of the line, so a line on a strong texture might be less visible than a line on a uniform field. To test this hypothesis, white lines were printed on fields with different texture contrasts, and we measured the threshold visibility for detecting the line.The line was printed as a reflectance increment in one of the pixel-rows of an error-diffusion pattern. The error diffusion-pattern was produced by applying the Floyd and Steinberg algorithm to a gray square. Two experiments were conducted. In one experiment, only the contrast of the halftone pattern was varied, and the subject was required to detect the pattern. In the second experiment, both the contrast of the halftone pattern and the contrast of the line were varied, and the subject was required to detect the line. The threshold for detecting the line was then plotted as a function of the strength of the halftone.It was found that the error-diffusion halftone pattern does not mask sensitivity to a line until the halftone pattern was many times above its own detection strength. Even when the halftone pattern was at the highest contrast that could be printed (about 20 times threshold contrast), the threshold amplitude for detecting the line was only doubled. Error diffusion is typically used because it reduces the visibility of the halftone texture. Since only very strong halftone textures provided any visual masking, the contrast of the error diffusion texture had to be very high to obtain any significant masking effect. This has the unfortunate implication that objectionable banding may only be hidden with even more objectionable halftone texture. Some of the implications for modeling band visibility will be discussed. It is important to note that there are previously described halftone patterns that can physically reduce the amplitude of the bands, and the present result does not run counter to these findings.

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.

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.

High-quality image processing architecture for facsimiles

A total and coherent image processing architecture for G3/G4/ISDN facsimiles is proposed that features high-quality multi-level processing by means of correlative area scanning and a software-oriented processing architecture. This image processing LSI controller includes a resolution converter and error diffusion halftone processing circuits in 4000 gates. A semi-superfine scanning mode is evaluated, which will be adopted as a new CCITT G3 optional mode.