基于抗差错算术编码的不等差错保护图像传输方法

JPEG2000图像的分层特性要求采用不等差错保护方法以实现高效传输,本文提出了一种新型的不等差错保护方法,对不同位平面采用不同码率的抗差错算术码进行编码.与基于信道编码的不等差错保护方法相比,该方法保持了压缩码流的结构,避免了复杂的信道成帧过程.与已有的基于抗差错算术码的等差错保护方法相比,该方法提高了传输图像的质量.     

Error Protection and Interleaving for Wireless Transmission of JPEG 2000 Images and Video

The transmission of JPEG 2000 images or video over wireless channels has to cope with the high probability and burstyness of errors introduced by Gaussian noise, linear distortions, and fading. At the receiver side, there is distortion due to the compression performed at the sender side, and to the errors introduced in the data stream by the channel. Progressive source coding can also be successfully exploited to protect different portions of the data stream with different channel code rates, based upon the relative importance that each portion has on the reconstructed image. Unequal error protection (UEP) schemes are generally adopted, which offer a close to the optimal solution. In this paper, we present a dichotomic technique for searching the optimal UEP strategy, which lends ideas from existing algorithms, for the transmission of JPEG 2000 images and video over a wireless channel. Moreover, we also adopt a method of virtual interleaving to be used for the transmission of high bit rate streams over packet loss channels, guaranteeing a large PSNR advantage over a plain transmission scheme. These two protection strategies can also be combined to maximize the error correction capabilities.     

JPEG2000的重要性编码

讨论一种利用图像重要性测度实现静态图像压缩标准JPEG2000编码方法。JPEG2000编码器的技术核心是离散小波变换和：EBCOT，而EBCOT是由两个编码引擎T1，T2组成的，其中T2编码主要是完成码流的组织，其方法是灵活多变的，用户可以根据特殊要求组织码流，只要码流的格式符合JPEG2000的格式即可。本文根据编码图像小波域的系数和时域的像素值计算该系数的重要性，并利用重要性组织完全符合JPEG2000格式的码流。可以利用标准JPEG2000解码器对本算法形成的码流进行解码。     

Scalable image and video transmission using irregular repeat-accumulate codes with fast algorithm for optimal unequal error protection

This paper considers designing and applying punctured irregular repeat-accumulate (IRA) codes for scalable image and video transmission over binary symmetric channels. IRA codes of different rates are obtained by puncturing the parity bits of a mother IRA code, which uses a systematic encoder. One of the main ideas presented here is the design of the mother code such that the entire set of higher rate codes obtained by puncturing are good. To find a good unequal error protection for embedded bit streams, we employ the fast joint source-channel coding algorithm in Hamzaoui et al. to minimize the expected end-to-end distortion. We test with two scalable image coders (SPIHT and JPEG-2000) and two scalable video coders (3-D SPIHT and H.26L-based PFGS). Simulations show better results with IRA codes than those reported in Banister et al. with JPEG-2000 and turbo codes. The IRA codes proposed here also have lower decoding complexity than the turbo codes used by Banister et al.     

结构信息最优的静止图像压缩算法研究

JPEG2000是基于小波变换的新一代静止图像压缩标准,与以往的压缩标准相比,其具有很多优点。但是JPEG2000以MSE作为图像失真评价标准,而MSE不能很好的符合人眼主观评分,进而很大地影响了JPEG2000的压缩性能。该文在JPEG2000标准框架下,提出了以结构相似度作为失真评价标准的静止图像压缩算法(SJPEG2000)。该算法以系数对图像结构信息贡献量的大小作为准则来截取码流,使压缩后的图像尽量保存原图像的结构信息。实验结果表明,该算法压缩得到的图像很好地保留了图像结构信息,压缩图像的主观质量得到提高,结构相似度值较原JPEG2000也有一定提高。     

JPEG2000实时截断码率控制新算法及其VLSI结构设计

提出一种实时编码实时截断的码率控制算法.它根据已分解的小波子带内码块有效位平面数来预测未分解的小波子带内码块有效位平面数,并根据编码通道数和小波/量化权系数为当前编码码块分配码率.并提出一种JPEG2000编码实时截断,两级码率控制的编码体系结构.第一级采用本文提出的算法实时截断码流和编码通道.第二级在低码率下采用JPEG2000标准的PCRD优化算法搜索精确的分层截断点.在最优分层截断之前多数码流和编码通道被预先截断,存储器损耗小,实时性高.低码率下,图像质量跟JPEG2000标准一致.     

Interlayer bit allocation for scalable video coding

In this paper, we present a theoretical analysis of the distortion in multilayer coding structures. Specifically, we analyze the prediction structure used to achieve temporal, spatial, and quality scalability of scalable video coding (SVC) and show that the average peak signal-to-noise ratio (PSNR) of SVC is a weighted combination of the bit rates assigned to all the streams. Our analysis utilizes the end user's preference for certain resolutions. We also propose a rate-distortion (R-D) optimization algorithm and compare its performance with that of a state-of-the-art scalable bit allocation algorithm. The reported experiment results demonstrate that the R-D algorithm significantly outperforms the compared approach in terms of the average PSNR.     

Joint thresholding and quantizer selection for transform imagecoding: entropy-constrained analysis and applications to baseline JPEG

Striving to maximize baseline (Joint Photographers Expert Group-JPEG) image quality without compromising compatibility of current JPEG decoders, we develop an image-adaptive JPEG encoding algorithm that jointly optimizes quantizer selection, coefficient "thresholding", and Huffman coding within a rate-distortion (R-D) framework. Practically speaking, our algorithm unifies two previous approaches to image-adaptive JPEG encoding: R-D optimized quantizer selection and R-D optimal thresholding. Conceptually speaking, our algorithm is a logical consequence of entropy-constrained vector quantization (ECVQ) design principles in the severely constrained instance of JPEG-compatible encoding. We explore both viewpoints: the practical, to concretely derive our algorithm, and the conceptual, to justify the claim that our algorithm approaches the best performance that a JPEG encoder can achieve. This performance includes significant objective peak signal-to-noise ratio (PSNR) improvement over previous work and at high rates gives results comparable to state-of-the-art image coders. For example, coding the Lena image at 1.0 b/pixel, our JPEG encoder achieves a PSNR performance of 39.6 dB that slightly exceeds the quoted PSNR results of Shapiro's wavelet-based zero-tree coder. Using a visually based distortion metric, we can achieve noticeable subjective improvement as well. Furthermore, our algorithm may be applied to other systems that use run-length encoding, including intraframe MPEG and subband or wavelet coding.     

基于ADV212的实时图像压缩系统

采用专用图像压缩芯片ADV212设计了一个能对分辨力高、数据量大的图像进行实时压缩的系统.该系统能够根据输入数据率自适应调整压缩比,实时产生JPEG2000格式的码流.ADV212输出的码流经过加密后可以实时输出也可在本系统内存储.实验结果表明,该系统能满足实时性要求,同时所得重建图像具有较好的主观视觉感受和较高的峰值信噪比.     

Rate distortion optimal bit allocation methods for volumetric data using JPEG 2000.

Computer modeling programs that generate three-dimensional (3-D) data on fine grids are capable of generating very large amounts of information. These data sets, as well as 3-D sensor/measured data sets, are prime candidates for the application of data compression algorithms. A very flexible and powerful compression algorithm for imagery data is the newly released JPEG 2000 standard. JPEG 2000 also has the capability to compress volumetric data, as described in Part 2 of the standard, by treating the 3-D data as separate slices. As a decoder standard, JPEG 2000 does not describe any specific method to allocate bits among the separate slices. This paper proposes two new bit allocation algorithms for accomplishing this task. The first procedure is rate distortion optimal (for mean squared error), and is conceptually similar to postcompression rate distortion optimization used for coding codeblocks within JPEG 2000. The disadvantage of this approach is its high computational complexity. The second bit allocation algorithm, here called the mixed model (MM) approach, mathematically models each slice's rate distortion curve using two distinct regions to get more accurate modeling at low bit rates. These two bit allocation algorithms are applied to a 3-D Meteorological data set. Test results show that the MM approach gives distortion results that are nearly identical to the optimal approach, while significantly reducing computational complexity.     

基于自适应下采样和超分重建的图像压缩框架

针对联合图像专家组(JPEG)标准设计了一种基于自适应下采样和超分辨力重建的图像压缩编码框架。在编码器端,为待编码的原始图像设计了多种不同的下采样模式和量化模式,通过率失真优化算法从多种模式中选择最优的下采样模式(DSM)和量化模式(QM),最后待编码图像将在选择的模式下进行下采样和JPEG编码;在解码器端,采用基于卷积神经网络的超分辨力重建算法对解码后的下采样图像进行重建。此外,所提出的框架扩展到JPEG2000压缩标准下同样有效可行。仿真实验结果表明,相比于主流的编解码标准和先进的编解码方法,提出的框架能有效地提升编码图像的率失真性能,并能获得更好的视觉效果。     

Joint source/channel coding for image transmission with JPEG2000 over memoryless channels.

The high compression efficiency and various features provided by JPEG2000 make it attractive for image transmission purposes. A novel joint source/channel coding scheme tailored for JPEG2000 is proposed in this paper to minimize the end-to-end image distortion within a given total transmission rate through memoryless channels. It provides unequal error protection by combining the forward error correction capability from channel codes and the error detection/localization functionality from JPEG2000 in an effective way. The proposed scheme generates quality scalable and error-resilient codestreams. It gives competitive performance with other existing schemes for JPEG2000 in the matched channel condition case and provides more graceful quality degradation for mismatched cases. Furthermore, both fixed-length source packets and fixed-length channel packets can be efficiently formed with the same algorithm.     

Perceptual Color Image Coding With JPEG2000

A perceptual color image coder (PCIC) is presented for the $YC_{b}C_{r}$ color space within the framework of JPEG2000. This coder employs a vision model based perceptual distortion metric (PDM) to approximate perceived error for rate-distortion (R-D) optimization in order to maximize the visual quality of coded images. The vision model employed in the PCIC is structurally based on an existing monochromatic multichannel vision model, which is extended for color image coding. Subjective tests with 30 viewers show that the PCIC provides superior picture quality at low to intermediate bitrates in comparison with a JPEG2000 compliant coder employing the mean squared error (MSE) and the visual distortion metric (Cvis) as distortion measures, respectively.      

Rate-distortion optimized tree-structured compression algorithms for piecewise polynomial images.

This paper presents novel coding algorithms based on tree-structured segmentation, which achieve the correct asymptotic rate-distortion (R-D) behavior for a simple class of signals, known as piecewise polynomials, by using an R-D based prune and join scheme. For the one-dimensional case, our scheme is based on binary-tree segmentation of the signal. This scheme approximates the signal segments using polynomial models and utilizes an R-D optimal bit allocation strategy among the different signal segments. The scheme further encodes similar neighbors jointly to achieve the correct exponentially decaying R-D behavior (D(R) - c(o)2(-c1R)), thus improving over classic wavelet schemes. We also prove that the computational complexity of the scheme is of O(N log N). We then show the extension of this scheme to the two-dimensional case using a quadtree. This quadtree-coding scheme also achieves an exponentially decaying R-D behavior, for the polygonal image model composed of a white polygon-shaped object against a uniform black background, with low computational cost of O(N log N). Again, the key is an R-D optimized prune and join strategy. Finally, we conclude with numerical results, which show that the proposed quadtree-coding scheme outperforms JPEG2000 by about 1 dB for real images, like cameraman, at low rates of around 0.15 bpp.     

Improved Resolution Scalability for Bilevel Image Data in JPEG2000

In this paper, we address issues concerning bilevel image compression using JPEG2000. While JPEG2000 is designed to compress both bilevel and continuous tone image data using a single unified framework, there exist significant limitations with respect to its use in the lossless compression of bilevel imagery. In particular, substantial degradation in image quality at low resolutions severely limits the resolution scalable features of the JPEG2000 code-stream. We examine these effects and present two efficient methods to improve resolution scalability for bilevel imagery in JPEG2000. By analyzing the sequence of rounding operations performed in the JPEG2000 lossless compression pathway, we introduce a simple pixel assignment scheme that improves image quality for commonly occurring types of bilevel imagery. Additionally, we develop a more general strategy based on the JPIP protocol, which enables efficient interactive access of compressed bilevel imagery. It may be noted that both proposed methods are fully compliant with Part 1 of the JPEG2000 standard.      

Context-based entropy coding of block transform coefficients for image compression

It has been well established that state-of-the-art wavelet image coders outperform block transform image coders in the rate-distortion (R-D) sense by a wide margin. Wavelet-based JPEG2000 is emerging as the new high-performance international standard for still image compression. An often asked question is: how much of the coding improvement is due to the transform and how much is due to the encoding strategy? Current block transform coders such as JPEG suffer from poor context modeling and fail to take full advantage of correlation in both space and frequency sense. This paper presents a simple, fast, and efficient adaptive block transform image coding algorithm based on a combination of prefiltering, postfiltering, and high-order space-frequency context modeling of block transform coefficients. Despite the simplicity constraints, coding results show that the proposed coder achieves competitive R-D performance compared to the best wavelet coders in the literature.     

JPEG2000: standard for interactive imaging

JPEG2000 is the latest image compression standard to emerge from the Joint Photographic Experts Group (JPEG) working under the auspices of the International Standards Organization. Although the new standard does offer superior compression performance to JPEG, JPEG2000 provides a whole new way of interacting with compressed imagery in a scalable and interoperable fashion. This paper provides a tutorial-style review of the new standard, explaining the technology on which it is based and drawing comparisons with JPEG and other compression standards. The paper also describes new work, exploiting the capabilities of JPEG2000 in client-server systems for efficient interactive browsing of images over the Internet.     

基于人眼感知预测的JPEG2000码率控制算法

基于小波域的JPEG2000压缩编码算法,对重建图像造成的失真是结构信息的丢失,从而使人眼的图像感知质量下降。为了解决这个问题,该文提出一种基于人眼感知预测的JPEG2000码率控制算法(SIRA),首先提出了一种度量图像感知质量下降的参数模型,然后建立了一个能在编码之前预测JPEG2000压缩图像感知质量下降的单端预测模型,基于预测模型实现了JPEG2000标准的码率分配。仿真实验结果验证了模型的正确性及算法的有效性。     

Adaptive compression of medical ultrasound images

An adaptive image-coding algorithm for compression of medical ultrasound (US) images in the wavelet domain is presented. First, it is shown that the histograms of wavelet coefficients of the subbands in the US images are heavy-tailed and can be better modelled by using the generalised Student's t-distribution. Then, by exploiting these statistics, an adaptive image coder named JTQVS-WV is designed, which unifies the two approaches to image-adaptive coding: rate-distortion (R-D) optimised quantiser selection and R-D optimal thresholding, and is based on the varying-slope quantisation strategy. The use of varying-slope quantisation strategy (instead of fixed R-D slope) allows coding of the wavelet coefficients across various scales according to their importance for the quality of reconstructed image. The experimental results show that the varying-slope quantisation strategy leads to a significant improvement in the compression performance of the JTQVS-WV over the best state-of-the-art image coder, SPIHT, JPEG2000 and the fixed-slope variant of JTQVS-WV named JTQ-WV. For example, the coding of US images at 0.5 bpp yields a peak signal-to-noise ratio gain of >0.6, 3.86 and 0.3 dB over the benchmark, SPIHT, JPEG2000 and JTQ-WV, respectively.