基于塔式格型矢量量化的图像多描述编码算法

多描述编码(MDC)是解决差错信道上图像通信数据包丢失问题的一种新方法，它通过将图像分解为多个独立而又具有一定相关性的描述，并通过不同的信道进行传输，来改善数据丢失条件下的图像解码质量。本文提出了一种图像信号的多描述塔式格型矢量量化编码算法(MDPLVQ)，利用小波树之间的独立性，采用不同的塔式格型矢量量化缩放因子对小波系数进行量化。该算法设计简单，对冗余度的控制容易，实验结果说明了其有效性，其编码压缩性能优于多描述标量量化(MDSQ)、多描述对变换(MDPCT)和多描述零又树(MDEZW)等方法。     

X树非平衡保护多描述编码

本文提出了一种新的多描述图像编码方案X树非平衡保护多描述子带编码。首先把小波变换图像分解为结构信息和残余非零系数。其中结构信息包括非零系数的位置、符号和位数,是小波变换图像的关键信息,必须复制到每个描述。残余非零系数则通过多描述标量量化器生成两个索引分别放入不同的描述。两个描述通过不同的信道进行传输。由于每个描述都包含了图像的重要信息,因此,接收到一个信道的信息就可以重建出一定质量的图像。如果所有的信道传输的信息都被接收,就会得到比任何一个单独信道更好的重建图像。实验结果验证了本算法的有效性和正确性。     

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。     

基于小波变换的图像快速压缩算法

结合目前广泛采用的嵌入式小波零树编码(EZW)和分层树集划分算法(SPIHT),提出了一种适用于图像小波变换高频压缩的提升算法.在经小波变换之后的矩阵中引入区间变化的概念,选取合适的数值取代区间中的数值,之后进行编码和传输.对于小波变换之后的图像在低频部分采用了DPCM算法,在高频部分采用了在EZW和SPIHT基础上改进的快速压缩算法,那么在编码时就可以用较短的时间保留原始图像的大部分能量,这对大幅图像的压缩和传输非常有利.虽然新算法与原先两种算法相比略微损失了部分保真度,但却在很大层度上降低了计算复杂度,缩短了编码时间.实验结果表明,此算法取得了较好的效果.     

基于H.264和双树小波的多描述视频编码

本文针对互联网和无线信道等不可靠网络的视频传输问题,提出一种基于H.264和双树小波变换的多描述视频编码解决方案.采用分层的多描述视频编码框架,实现H.264和双树小波编码的有机结合.基本层用H.264编码器对视频信号进行低码率编码后,复制到各个描述;增强层用三维双树小波变换对原视频和基本层重建视频的差值进行编码,将产生的四棵三维小波树经噪声整形后两两组合,编码送到不同描述.在解码端,若能够接收到两个描述,则通过中心解码器实现高质量的视频重建;若丢失一个描述,则通过边解码器解码仍可保证一定质量的视频重建.实验结果表明在相同码率下,本算法的视频中心解码和边解码质量优于现有的多描述视频编码算法.     

一种适用于丢包信道的小波编码图像传输方案

该文提出一种适用于丢包信道的基于小波变换的可伸缩图像编码传输方案。该方案利用分层多描述编码来提高信源编码的容错性能,利用信道编码来提高系统整体的抗丢包性能,采用编码后率失真优化技术对信源编码进行优化。利用非系统的RS码对信源编码符号和信道编码符号进行重新排序,将分层多描述编码和信道编码进行了有效的结合。通过在编解码端采用相同的排序算法,来减少传输开销。仿真结果表明,该方案与现有的方案相比,提高了接收图像的质量,并且需要较少的传输开销。     

高分辨率航测CCD图像的无损压缩算法

针对超高分辨率CCD相机拍摄图像,提出了一种无损压缩算法.算法以嵌入式小波零树编码为基础, 通过对零树编码输出的比特平面采用变长游程编码方法很好地提高了图像压缩比.同时,算法将游程编码与比特平面编码统一进行,编码效率大大提高.实验结果表明,该算法的像素平均比特率相对经典的嵌入式小波零树算法均有明显降低.     

基于LDPC码的小波图像传输码率优化

LDPC码是一种具有低复杂度,强纠错能力的信道分组编码结构,SPIHT算法是嵌入式小波图像压缩编码中性能较好的一种。文中充分考虑SPIHT算法和LDPC码的特性,提出了根据信源编码后的数据在解码重建时的重要程度进行不等纠错保护的信源信道联合编码方案。实验表明,该方案有利于压缩图像在噪声信道上的可靠传输,提高系统整体纠错性能。     

一种基于小波变换的遥测图像编码新方法

为了实现火箭遥测图像的高效处理,优化火箭遥测图像的编码流程,提出了一种基于小波变换的火箭遥测图像编码新方法。在图像小波变换的基础上,以空间方向树为编码单位,采用改进的分层树集合分割(SPIHT)算法实现图像重要小波系数的比特平面编码,并采用联合码率优化截取方法,优先截取和传输重要比特平面的遥测图像数据。通过系统测试,结果表明：与传统的火箭遥测图像编码方法相比,新的遥测图像编码方法具有丢帧率低、重构图像质量好、编码效率高等优点,满足运载火箭遥测图像处理和传输的工程需求。     

小波编码图像联合信源信道解码算法的研究

为提高图像在噪声信道中传输的可靠性,该文提出了一种图像联合信源信道解码方案。信源图像首先经离散小波变换,压缩编码。编码数据经RCPC(率兼容删余卷积码)信道编码保护,通过噪声信道传输。在接收端的改进的APRI-SOVA (先验信息软输出维特比算法)在信道解码时,不仅利用了信道输出的软判决,而且进一步利用了信源解码器提供的当前解码的比特的可靠性信息。仿真结果显示,有效利用信源数据中遗留的相关性,能够实现图像解码质量的提高。     

基于零块编码的小波图像多表达容错压缩方法

本文提出一种均衡小波图像多表达容错压缩方法－MD－EZBC算法。这种方法将图像压缩为一系列可独立传输和解码的多表达了编码，无需优先级的支持也可充分利用不可靠信道的传输带宽。实验表明，本文方法不仅有很好的压缩效率，同时能够把传输错误图像噪声均匀地分布于整个空间，获得稳定的图像质量。     

SAR image data compression using a tree-structured wavelettransform

SAR image compression is very important in reducing the costs of data storage and transmission in relatively slow channels. The authors propose a compression scheme driven by texture analysis, homogeneity mapping and speckle noise reduction within the wavelet framework. The image compressibility and interpretability are improved by incorporating speckle reduction into the compression scheme. The authors begin with the classical set partitioning in hierarchical trees (SPIHT) wavelet compression scheme, and modify it to control the amount of speckle reduction, applying different encoding schemes to homogeneous and nonhomogeneous areas of the scene. The results compare favorably with the conventional SPIHT wavelet and the JPEG compression methods     

Wavelet tree classification and hybrid coding for image compression

A hybrid coding system that uses a combination of set partition in hierarchical trees (SPIHT) and vector quantisation (VQ) for image compression is presented. Here, the wavelet coefficients of the input image are rearranged to form the wavelet trees that are composed of the corresponding wavelet coefficients from all the subbands of the same orientation. A simple tree classifier has been proposed to group wavelet trees into two classes based on the amplitude distribution. Each class of wavelet trees is encoded using an appropriate procedure, specifically either SPIHT or VQ. Experimental results show that advantages obtained by combining the superior coding performance of VQ and efficient cross-subband prediction of SPIHT are appreciable for the compression task, especially for natural images with large portions of textures. For example, the proposed hybrid coding outperforms SPIHT by 0.38 dB in PSNR at 0.5 bpp for the Bridge image, and by 0.74 dB at 0.5 bpp for the Mandrill image.     

A fast and efficient hybrid fractal-wavelet image coder.

The excellent visual quality and compression rate of fractal image coding have limited applications due to exhaustive inherent encoding time. This paper presents a new fast and efficient image coder that applies the speed of the wavelet transform to the image quality of the fractal compression. Fast fractal encoding using Fisher's domain classification is applied to the lowpass subband of wavelet transformed image and a modified set partitioning in hierarchical trees (SPIHT) coding, on the remaining coefficients. Furthermore, image details and wavelet progressive transmission characteristics are maintained, no blocking effects from fractal techniques are introduced, and the encoding fidelity problem common in fractal-wavelet hybrid coders is solved. The proposed scheme promotes an average of 94% reduction in encoding-decoding time comparing to the pure accelerated Fractal coding results. The simulations also compare the results to the SPIHT wavelet coding. In both cases, the new scheme improves the subjective quality of pictures for high-medium-low bitrates.     

一种高效的多描述容错编码方案

针对JPEG2000标准所提供的容错编码工具的局限性,提出了把多描述编码运用于小波变换系数当中,产生图像的多个压缩编码描述的方案,该方案进一步提高压缩编码图像的容错性能。实验表明,此方案提供了更好的容错性能,非常适于网络中的图像传输。     

基于人眼视觉特性的ROI渐进编码算法

一般基于感兴趣区域(ROI)的图像编码算法都没有充分考虑人眼视觉特性,在分析了JPEG2000中感兴趣区域编码的优缺点后,利用小波变换的特点并结合人眼视觉的掩蔽效应,提出了一种改进的ROI图像编码算法。首先将图像小波域中的所有低频系数进行移位处理,而对于小波域中的高频系数,仅对其属于ROI区域的系数进行移位处理,再利用等级树集合分割(SPIHT)算法进行编码传输。仿真实验证明了该算法比原有算法的图像主观质量更好。     

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.     

Content-based multiple bitstream image transmission over noisy channels

We propose a novel combined source and channel coding scheme for image transmission over noisy channels. The main feature of the proposed scheme is a systematic decomposition of image sources so that unequal error protection can be applied according to not only bit error sensitivity but also visual content importance. The wavelet transform is adopted to hierarchically decompose the image. The association between the wavelet coefficients and what they represent spatially in the original image is fully exploited so that wavelet blocks are classified based on their corresponding image content. The classification produces wavelet blocks in each class with similar content and statistics, therefore enables high performance source compression using the set partitioning in hierarchical trees (SPIHT) algorithm. To combat the channel noise, an unequal error protection strategy with rate-compatible punctured convolutional/cyclic redundancy check (RCPC/CRC) codes is implemented based on the bit contribution to both peak signal-to-noise ratio (PSNR) and visual quality. At the receiving end, a postprocessing method making use of the SPIHT decoding structure and the classification map is developed to restore the degradation due to the residual error after channel decoding. Experimental results show that the proposed scheme is indeed able to provide protection both for the bits that are more sensitive to errors and for the more important visual content under a noisy transmission environment. In particular, the reconstructed images illustrate consistently better visual quality than using the single-bitstream-based schemes.