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.     

Inverse halftoning and kernel estimation for error diffusion

Two different approaches in the inverse halftoning of error-diffused images are considered. The first approach uses linear filtering and statistical smoothing that reconstructs a gray-scale image from a given error-diffused image. The second approach can be viewed as a projection operation, where one assumes the error diffusion kernel is known, and finds a gray-scale image that will be halftoned into the same binary image. Two projection algorithms, viz., minimum mean square error (MMSE) projection and maximum a posteriori probability (MAP) projection, that differ on the way an inverse quantization step is performed, are developed. Among the filtering and the two projection algorithms, MAP projection provides the best performance for inverse halftoning. Using techniques from adaptive signal processing, we suggest a method for estimating the error diffusion kernel from the given halftone. This means that the projection algorithms can be applied in the inverse halftoning of any error-diffused image without requiring any a priori information on the error diffusion kernel. It is shown that the kernel estimation algorithm combined with MAP projection provide the same performance in inverse halftoning compared to the case where the error diffusion kernel is known.     

Modeling and quality assessment of halftoning by error diffusion

Digital halftoning quantizes a graylevel image to one bit per pixel. Halftoning by error diffusion reduces local quantization error by filtering the quantization error in a feedback loop. In this paper, we linearize error diffusion algorithms by modeling the quantizer as a linear gain plus additive noise. We confirm the accuracy of the linear model in three independent ways. Using the linear model, we quantify the two primary effects of error diffusion: edge sharpening and noise shaping. For each effect, we develop an objective measure of its impact on the subjective quality of the halftone. Edge sharpening is proportional to the linear gain, and we give a formula to estimate the gain from a given error filter. In quantifying the noise, we modify the input image to compensate for the sharpening distortion and apply a perceptually weighted signal-to-noise ratio to the residual of the halftone and modified input image. We compute the correlation between the residual and the original image to show when the residual can be considered signal independent. We also compute a tonality measure similar to total harmonic distortion. We use the proposed measures for edge sharpening, noise shaping, and tonality to evaluate the quality of error diffusion algorithms.     

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.     

Adaptive error diffusion method for image quantisation

An adaptive error diffusion method for image quantisation is presented. The error filter coefficients are adapted using a generalised two-dimensional LMS algorithm and the quantisation scale is calculated on the basis of the image histogram. The developed method provides a minimum reconstruction error, a decrease in false contours in the homogeneous areas and precise reproduction of the edges in the output image.<>     

Wavelet-based inverse halftoning for error diffused halftones

This paper describes a technique for inverse halftoning based on the wavelet domain deconvolution that comprises Fourier-domain followed by wavelet-domain noise suppression, in order to benefit from the advantages of each of them. The proposed algorithm can be formulated as a linear deconvolution problem. In fact, we model such a gray-scale image to be the result of a convolution of the original image with a point spread function (PSF) and a colored noise. Our method performs inverse halftoning by first inverting the model specified convolution operator and then attenuating the residual noise using scalar wavelet-domain shrinkage. Using simulations, we verify that the proposed method is competitive with state-of-the-art inverse halftoning techniques in the mean-square-sense and that has also good visual performance. We illustrate the results with simulations on some examples.     

Threshold modulation and stability in error diffusion

Many modifications to error diffusion have been proposed to improve the algorithm and to extend its application to print media and to color. In this article, we describe some of the lessons that have been learned in two areas of error-diffusion research: threshold modulation and error stability. Both of these areas are important in understanding how to improve and extend the algorithm. Many suggested modifications have been made over the years to eliminate these unwanted textures. One method to improve the algorithm involves different ways of calculating and distributing the errors. Some of the modified algorithms have even proposed amplifying or suppressing the errors. Strange effects can occur, however, when the errors are amplified or if negative components are introduced. The stability analysis presented in this article will illustrate these instabilities and explain their relationship to changes in the error distribution.     

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.     

Adaptive wavelet threshold for image denoising

Threshold selection is the critical issue in image denoising via wavelet shrinkage. Many powerful approaches have been investigated, but few have been to make the threshold values adaptive to the changing statistics of images and meanwhile maintain the efficiency of the algorithm. In this work an efficient adaptive algorithm to capture the dependency of inter-scale wavelet coefficients is proposed. Experiments show that higher peak signal-to-noise ratio can be obtained as compared to other threshold-denoising algorithms.     

TD-SCDMA系统的自适应门限接力切换

目前的接力切换技术是在理想化条件下的模型,在现实环境的一些特殊情况下,不利于高效地利用信道资源,针对这些特殊情况提出了基于移动台移动速度的自适应切换门限接力切换,在系统切换呼叫到达率较高时,能有效地降低用户接力切换呼叫的阻塞概率,高效地利用信道资源,扩大了系统容量,从整体上提高了系统接力切换的服务质量（QoS）.     

Tone-dependent error diffusion

We present an enhanced error diffusion halftoning algorithm for which the filter weights and the quantizer thresholds vary depending on input pixel value. The weights and thresholds are optimized based on a human visual system model. Based on an analysis of the edge behavior, a tone dependent threshold is designed to reduce edge effects and start-up delay. We also propose an error diffusion system with parallel scan that uses variable weight locations to reduce worms.     

Fuzzy error diffusion

Quantization errors are generally hidden by performing a dithering operation on the image. A common method is to utilize error diffusion. However, this method is prone to error accumulation, resulting in color impulses and streaks. This paper presents a new approach to error diffusion dithering through a fuzzy error diffusion algorithm. In this method, the amount of error to be diffused is determined by considering the relative location of the pixel not only to the closest codebook vector, but to all other palette entries. The goal is to hide the quantization errors by error diffusion, while preventing the excess accumulation of errors. This is achieved through an attraction-repulsion schema according to a fuzzy membership function. We also explored methods to speed up the fuzzy error diffusion process through a L-filter approach by determining a fixed set of membership values. We have implemented the fuzzy error diffusion algorithm for color images and achieved drastic improvements, resulting in superior quality dithered images and significantly lower mean squared error values. A different error measure modeling the characteristic of the human visual system also indicates the superiority of our method.     

Adaptive threshold control scheme for packet acquisition

An adaptive threshold control scheme for packet acquisition is described. The threshold control is done adaptively by setting the threshold proportional to the maximum likelihood estimate of the noise power     

Adaptive turbo-coded modulation for flat-fading channels

We consider a turbo-coded system employed on a flat-fading channel where the transmitter and receiver adapt the encoder, decoder, modulation scheme, and transmit power to the state of the channel. Assuming instantaneous and error-free channel gain and phase knowledge at the transmitter and the receiver, we determine the optimal adaptation strategy that maximizes the throughput of this system, while achieving a given bit-error rate under an average power constraint. Our optimized adaptive modulation strategy is based on an extensive set of existing turbo-coded modulation schemes. We find that adapting both the turbo encoder (rate) and the transmit power can achieve performance within 3 dB of the fading channel capacity.     

Adaptive coded modulation for fading channels

We apply coset codes to adaptive modulation in fading channels. Adaptive modulation is a powerful technique to improve the energy efficiency and increase the data rate over a fading channel. Coset codes are a natural choice to use with adaptive modulation since the channel coding and modulation designs are separable. Therefore, trellis and lattice codes designed for additive white Gaussian noise (AWGN) channels can be superimposed on adaptive modulation for fading channels, with the same approximate coding gains. We first describe the methodology for combining coset codes with a general class of adaptive modulation techniques. We then apply this methodology to a spectrally efficient adaptive M-ary quadrature amplitude modulation (MQAM) to obtain trellis-coded adaptive MQAM. We present analytical and simulation results for this design which show an effective coding gain of 3 dB relative to uncoded adaptive MQAM for a simple four-state trellis code, and an effective 3.6-dB coding gain for an eight-state trellis code. More complex trellis codes are shown to achieve higher gains. We also compare the performance of trellis-coded adaptive MQAM to that of coded modulation with built-in time diversity and fixed-rate modulation. The adaptive method exhibits a power savings of up to 20 dB     

Adaptive delta modulation

An adaptive-delta-modulation system is described taking advantage of the storage of the line digit pattern in the holding register of a delayed-delta-modulation system, to produce a significant improvement in signal/quantisation-noise ratio.     

Row-oriented multiscale error diffusion technique for digitalhalftoning

A digital halftoning method is proposed to diffuse error with a more symmetric error distribution by making use of the concept of multiscale error diffusion. The method can improve the diffusion performance by effectively reducing directional hysteresis. The diffusion is row-oriented rather than frame-oriented and hence can reduce the latency and computational effort as compared with conventional multiscale error diffusion schemes. This makes it possible for real-time applications     

Embedded multilevel error diffusion

We present an algorithm for image browsing systems that embeds the output of binary Floyd-Steinberg (1975) error diffusion, or a low bit-depth gray-scale or color error diffused image into higher bit-depth gray-scale or color error diffused images. The benefits of this algorithm are that a low bit-depth halftoned image can be directly obtained from a higher bit-depth halftone for printing or progressive transmission simply by masking one or more bits off of the higher bit-depth image. The embedding can be done in any bits of the output, although the most significant or the least significant bits are most convenient. Due to constraints on the palette introduced by embedding, the image quality for the higher bit-depth halftone may be reduced. To preserve the image quality, we present algorithms for color palette organization, or binary index assignment, to be used as a preprocessing step to the embedding algorithm.