Hybrid fractal zerotree wavelet image coding

In this paper, a hybrid fractal zerotree wavelet (FZW) image coding algorithm is proposed. The algorithm couples a zerotree-based encoder, such as the embedded zerotree wavelet (EZW) coder or set partitioning in hierarchical trees, and a fractal image coder; this coupling is done in the wavelet domain. Based on perceptually-weighted distortion-rate calculations, a fractal method is adaptively applied to the parts of an image that can be encoded more efficiently relative to an EZW coder at a given rate. In addition to improving compression performance, the proposed algorithm also allows one to impose desirable properties from each type of image coder, such as progressive transmission, the zerotree structure, and range-domain block decoding.     

A NEW FRACTAL ZEROTREE CODING FOR WAVELET IMAGE

Based on the mechanisms underlying the performance of fractal and Discrete Wavelet Transform(DWT), one method using fractal-based self-quantization coding way to code different subband coefficients of DWT is presented. Within this method finer coefficients are fractal encoded according to the successive coarser ones. Self-similarities inherent between parent and their children at the same spatial location of the adjacent scales of similar orientation are exploited to predict variation of information across wavelet scales. On the other hand, with respect to Human Visual System(HVS) model, we assign different error thresholds to different decomposition scales, and different shape of range blocks to different orientations of the same scale, by which the perceptually lossless high compression ratio can be achieved and the matching processing can be quickened dramatically.     

Hierarchical quantization indexing for wavelet and wavelet packet image coding

In this paper, we introduce the quantization index hierarchy, which is used for efficient coding of quantized wavelet and wavelet packet coefficients. A hierarchical classification map is defined in each wavelet subband, which describes the quantized data through a series of index classes. Going from bottom to the top of the tree, neighboring coefficients are combined to form classes that represent some statistics of the quantization indices of these coefficients. Higher levels of the tree are constructed iteratively by repeating this class assignment to partition the coefficients into larger subsets. The class assignments are optimized using a rate-distortion cost analysis. The optimized tree is coded hierarchically from top to bottom by coding the class membership information at each level of the tree. Context-adaptive arithmetic coding is used to improve coding efficiency. The developed algorithm produces PSNR results that are better than the state-of-art wavelet-based and wavelet packet-based coders in literature.     

Adaptive wavelet packet based image coding with optimalentropy-constrained lattice vector quantizer (ECLVQ)

In this work, wavelet basis and source coding are jointly optimized, while specifying the source coding strategy as entropy-constrained lattice vector quantizer (ECLVQ). The presented approach differs from previous works in which the choice of wavelet basis is quasioptimal, but the quantizer set is optimally chosen     

基于最优小波分组的联合信源信道编码图像传输系统

提出了一种适用于图像传输的,且在率失真意义上最优的小波分组分解的图像编码算法,不同于一般的小波分组图像编码,所提出的图像编码器将信道信息及信道编码情况考虑到信源编码中来,从而实现联合信源信道编码。小波分组子带编码采用位平面编码的方式,从而可以很好地结合不等差错保护(UEP)传输。提出了结合重量递增校验矩阵的LDPC码(WICP-LDPC)进行图像传输的方案。在BSC信道上的仿真实验表明,所提出的方法要优于使用均等差错保护的传输方案,并且所提出的传输系统在性能上也优于近几年来新提出的几种图像联合编码传输系统。     

Adaptive directional lifting-based wavelet transform for image coding.

We present a novel 2-D wavelet transform scheme of adaptive directional lifting (ADL) in image coding. Instead of alternately applying horizontal and vertical lifting, as in present practice, ADL performs lifting-based prediction in local windows in the direction of high pixel correlation. Hence, it adapts far better to the image orientation features in local windows. The ADL transform is achieved by existing 1-D wavelets and is seamlessly integrated into the global wavelet transform. The predicting and updating signals of ADL can be derived even at the fractional pixel precision level to achieve high directional resolution, while still maintaining perfect reconstruction. To enhance the ADL performance, a rate-distortion optimized directional segmentation scheme is also proposed to form and code a hierarchical image partition adapting to local features. Experimental results show that the proposed ADL-based image coding technique outperforms JPEG 2000 in both PSNR and visual quality, with the improvement up to 2.0 dB on images with rich orientation features.     

Universal perceptual weighted zerotree coding for image and videocompression

A universal representation for the perceptual weighted zerotree coding algorithm is developed, in which the perceptual weighted zerotree coding is decomposed into two separate parts, i.e. visual weighting and zerotree representation, which can be realised independently. Prior to zerotree processing, the extracted full-tree is weighted by using a visual weighting matrix. Any zerotree algorithm like EZW, SPIHT and zerotree space-frequency quantisation can be used to encode the weighted coefficients of the wavelet transform. In other words, any previous algorithm without perceptual weighting can be easily extended to form a new perceptual coder using the proposed framework. Several examples of visual weighting matrices are given to show the effect of the new method     

基于多级零树编码的小波系数网格编码量化

该文提出了对小波图像作多级零树编码后进行网格编码量化（TCQ）的新方法。首先利用子带间的相关性进行零树编码，然后利用卷积编码和信号空间扩展来增大量化信号间的欧氏距离，并用Viterbi算法寻找最优量化序列。仿真结果表明，该方法比零树编码后采用最优量化要提高0．3dB左右。该方法还具有编码计算复杂度适中，解码简单的优点。     

Dilation-run wavelet image coding

The run-length coding and the morphological representation are two classical schemes for wavelet image coding. The run-length coders have the advantage of simplicity by recording the lengths of zero-runs between significant wavelet coefficients but at the expense of yielding an inferior rate-distortion performance. The morphology-based coders, on the other hand, utilize the morphological dilation operation to delineate the clusters of significant coefficients for improving coding performance. In this paper, a novel dilation-run image coding algorithm is developed by taking the advantages of both schemes, in which the clustered significant coefficients are extracted by using the morphological dilation operation and the insignificant coefficients between the extracted clusters are coded by using the run-length coding method. The proposed dilation-run image coder is implemented in the framework of bitplane coding for producing embedded bitstreams. Compared with several state-of-the-art wavelet image coding methods, the proposed dilation-run image coding method achieves comparable rate-distortion coding performance, especially more attractive for fingerprint type of imageries.     

Space-frequency quantization for wavelet image coding

A new class of image coding algorithms coupling standard scalar quantization of frequency coefficients with tree-structured quantization (related to spatial structures) has attracted wide attention because its good performance appears to confirm the promised efficiencies of hierarchical representation. This paper addresses the problem of how spatial quantization modes and standard scalar quantization can be applied in a jointly optimal fashion in an image coder. We consider zerotree quantization (zeroing out tree-structured sets of wavelet coefficients) and the simplest form of scalar quantization (a single common uniform scalar quantizer applied to all nonzeroed coefficients), and we formalize the problem of optimizing their joint application. We develop an image coding algorithm for solving the resulting optimization problem. Despite the basic form of the two quantizers considered, the resulting algorithm demonstrates coding performance that is competitive, often outperforming the very best coding algorithms in the literature.     

Fast adaptive wavelet packet image compression

Wavelets are ill-suited to represent oscillatory patterns: rapid variations of intensity can only be described by the small scale wavelet coefficients, which are often quantized to zero, even at high bit rates. Our goal is to provide a fast numerical implementation of the best wavelet packet algorithm in order to demonstrate that an advantage can be gained by constructing a basis adapted to a target image. Emphasis is placed on developing algorithms that are computationally efficient. We developed a new fast two-dimensional (2-D) convolution decimation algorithm with factorized nonseparable 2-D filters. The algorithm is four times faster than a standard convolution-decimation. An extensive evaluation of the algorithm was performed on a large class of textured images. Because of its ability to reproduce textures so well, the wavelet packet coder significantly out performs one of the best wavelet coder on images such as Barbara and fingerprints, both visually and in term of PSNR.     

Curved wavelet transform for image coding.

The conventional two-dimensional wavelet transform used in existing image coders is usually performed through one-dimensional (1-D) filtering in the vertical and horizontal directions, which cannot efficiently represent edges and lines in images. The curved wavelet transform presented in this paper is carried out by applying 1-D filters along curves, rather than being restricted to vertical and horizontal straight lines. The curves are determined based on image content and are usually parallel to edges and lines in the image to be coded. The pixels along these curves can be well represented by a small number of wavelet coefficients. The curved wavelet transform is used to construct a new image coder. The code-stream syntax of the new coder is the same as that of JPEG2000, except that a new marker segment is added to the tile headers. Results of image coding and subjective quality assessment show that the new image coder performs better than, or as well as, JPEG2000. It is particularly efficient for images that contain sharp edges and can provide a PSNR gain of up to 1.67 dB for natural images compared with JPEG2000.     

DSSS系统中自适应小波包干扰抵消器

本文提出了一种DSSS系统中基于小波包变换域的自适应干扰抵消算法（AWPT）,分析了小波包变抵抵消窄带干扰和脉冲干扰的机理,提出了优化准则和相应的自适应抵消算法,通过计算机仿真研究了其抗窄带和脉冲干扰的能力,并与传统的加窗DFT干扰抵消和子带变换干扰抵消作了比较。     

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.     

Wavelet packet image coding using space-frequency quantization

We extend our previous work on space-frequency quantization (SFQ) for image coding from wavelet transforms to the more general wavelet packet transforms. The resulting wavelet packet coder offers a universal transform coding framework within the constraints of filterbank structures by allowing joint transform and quantizer design without assuming a priori statistics of the input image. In other words, the new coder adaptively chooses the representation to suit the image and the quantization to suit the representation. Experimental results show that, for some image classes, our new coder gives excellent coding performance.     

适宜图像编码的双正交小波基的选择

提出一种新的选择适合图橡编码应用的双正交小波基的方法。通过用几个已证实是与图像编码密切相关的小波基评价标准对小波进行全面评价，选出了一些适宜图像编码应用的双正交小波基，并作了编码模拟检验。     

Nonlinear wavelet transforms for image coding via lifting

We investigate central issues such as invertibility, stability, synchronization, and frequency characteristics for nonlinear wavelet transforms built using the lifting framework. The nonlinearity comes from adaptively choosing between a class of linear predictors within the lifting framework. We also describe how earlier families of nonlinear filter banks can be extended through the use of prediction functions operating on a causal neighborhood of pixels. Preliminary compression results for model and real-world images demonstrate the promise of our techniques.     

Spatial coefficient partitioning for lossless wavelet image coding

In pyramidal wavelet representation, an image is decomposed into multiresolution and multifrequency subbands with sets of tree-structured coefficients, i.e. a spatial orientation tree which consists of coefficients at different resolutions and different orientations but associated with the same spatial location. The magnitudes of the coefficients in these trees measure the signal activity level of the corresponding spatial areas. A novel coefficient partitioning algorithm is introduced for splitting the coefficients into two sets using a spatial orientation tree data structure. By splitting the coefficients, the overall theoretical entropy is reduced due to the different probability distributions for the two coefficient sets. In the spatial domain, it is equivalent to identifying smooth regions of the image. A lossless coder based on this spatial coefficient partitioning has a better coding performance than other wavelet-based lossless image coders such as S + P and JPEG-2000.     

Improved embedded zerotree wavelet coder

An improved embedded zerotree wavelet (IEZW) is presented, which can significantly reduce the scanning and symbol redundancy of the existing EZW