Low complexity DCT-based distributed source coding with Gray code for hyperspectral images

To compress hyperspectral images, a low complexity discrete cosine transform （DCT）-based distributed source coding （DSC） scheme with Gray code is proposed. Unlike most of the existing DSC schemes, which utilize transform in spatial domain, the proposed algorithm applies transform in spectral domain. Set-partitioning-based approach is applied to reorganize DCT coefficients into waveletlike tree structure and extract the sign, refinement, and significance bitplanes. The extracted refinement bits are Gray encoded. Because of the dependency along the line dimension of hyperspectral images, low density paritycheck-（LDPC）-based Slepian-Wolf coder is adopted to implement the DSC strategy. Experimental results on airborne visible/infrared imaging spectrometer （AVIRIS） dataset show that the proposed paradigm achieves up to 6 dB improvement over DSC-based coders which apply transform in spatial domain, with significantly reduced computational complexity and memory storage.

METHOD OF VECTOR QUANTIZATION CODING USING RECTANGULAR TRANSFORM FOR IMAGE COMPRESSION

First of all a simple and practical rectangular transform is given,and then thevector quantization technique which is rapidly developing recently is introduced.We combinethe rectangular transform with vector quantization technique for image data compression.Thecombination cuts down the dimensions of vector coding.The size of the codebook can reasonablybe reduced.This method can reduce the computation complexity and pick up the vector codingprocess.Experiments using image processing system show that this method is very effective inthe field of image data compression.

Wavelet-Based Mixed-Resolution Coding Approach Incorporating with SPT for the Stereo Image

With the advances of display technology, three-dimensional(3-D) imaging systems are becoming increasingly popular. One way of stimulating 3-D perception is to use stereo pairs, a pair of images of the same scene acquired from different perspectives. Since there is an inherent redundancy between the images of a stereo pairs, data compression algorithms should be employed to represent stereo pairs efficiently. The proposed techniques generally use block-based disparity compensation. In order to get the higher compression ratio, this paper employs the wavelet-based mixed-resolution coding technique to incorporate with SPT-based disparity-compensation to compress the stereo image data. The mixed-resolution coding is a perceptually justified technique that is achieved by presenting one eye with a low-resolution image and the other with a high-resolution image. Psychophysical experiments show that the stereo image pairs with one high-resolution image and one low-resolution image provide almost the same stereo depth to that of a stereo image with two high-resolution images. By combining the mixed-resolution coding and SPT-based disparity-compensation techniques, one reference (left) high-resolution image can be compressed by a hierarchical wavelet transform followed by vector quantization and Huffman encoder. After two level wavelet decompositions, for the low-resolution right image and low-resolution left image, subspace projection technique using the fixed block size disparity compensation estimation is used. At the decoder, the low-resolution right subimage is estimated using the disparity from the low-resolution left subimage. A full-size reconstruction is obtained by upsampling a factor of 4 and reconstructing with the synthesis low pass filter. Finally, experimental results are presented, which show that our scheme achieves a PSNR gain (about 0.92dB) as compared to the current block-based disparity compensation coding techniques.

Wavelet Coding of Image Using Quadtree and Vector Entropy Coding

A new efficient method based on Quadtree Representation and Vector Entropy Coding (QRVEC) for encoding the wavelet transform coefficients of images is presented. In addition, how to flexibly control the coder’ s output bit rate is also investigated.

An image compression method for space multispectral time delay and integration charge coupled device camera

Multispectral time delay and integration charge coupled device （TDICCD） image compression requires a low- complexity encoder because it is usually completed on board where the energy and memory are limited. The Consultative Committee for Space Data Systems （CCSDS） has proposed an image data compression （CCSDS-IDC） algorithm which is so far most widely implemented in hardware. However, it cannot reduce spectral redundancy in mukispectral images. In this paper, we propose a low-complexity improved CCSDS-IDC （ICCSDS-IDC）-based distributed source coding （DSC） scheme for multispectral TDICCD image consisting of a few bands. Our scheme is based on an ICCSDS-IDC approach that uses a bit plane extractor to parse the differences in the original image and its wavelet transformed coefficient. The output of bit plane extractor will be encoded by a first order entropy coder. Low-density parity-check-based Slepian-Wolf （SW） coder is adopted to implement the DSC strategy. Experimental results on space multispectral TDICCD images show that the proposed scheme significantly outperforms the CCSDS-IDC-based coder in each band.

Novel region-based image compression method based on spiking cortical model

To get the high compression ratio as well as the high-quality reconstructed image, an effective image compression scheme named irregular segmentation region coding based on spiking cortical model（ISRCS） is presented. This scheme is region-based and mainly focuses on two issues. Firstly, an appropriate segmentation algorithm is developed to partition an image into some irregular regions and tidy contours, where the crucial regions corresponding to objects are retained and a lot of tiny parts are eliminated. The irregular regions and contours are coded using different methods respectively in the next step. The other issue is the coding method of contours where an efficient and novel chain code is employed. This scheme tries to find a compromise between the quality of reconstructed images and the compression ratio. Some principles and experiments are conducted and the results show its higher performance compared with other compression technologies, in terms of higher quality of reconstructed images, higher compression ratio and less time consuming.

高清图像通信中的带宽优化策略

文章探讨高清图像通信中的带宽优化策略,旨在提高图像传输效率与质量,降低带宽消耗。通过分析当前高清图像通信面临的问题,提出了包括选择合适的视频编码算法、应用数据压缩技术、采用动态码率调整技术、实施带宽分流与边缘计算以及采用双码流技术结合策略在内的多种优化方法。这些策略不仅能够有效减少数据传输量,而且能在有限带宽条件下保证高清图像的稳定传输,改善用户体验。

Source extension based on ε-entropy

It is known by entropy theory that image is a source correlated with a certain characteristic of probability. The entropy rate of the source and ε- entropy (rate-distortion function theory) are the information content to identify the characteristics of video images, and hence are essentially related with video image compression. They are fundamental theories of great significance to image compression, though impossible to be directly turned into a compression method. Based on the entropy theory and the image compression theory, by the application of the rate-distortion feature mathematical model and Lagrange multipliers to some theoretical problems in the H.264 standard, this paper presents a new the algorithm model of coding rate-distortion. This model is introduced into complete test on the capability of the test model of JM61e (JUT Test Model). The result shows that the speed of coding increases without significant reduction of the rate-distortion performance of the coder.

DATA COMPRESSION FOR CHINESE CHARACTERS USING TRANSFORM RUNLENGTH CODING

In the transmission of two-tone images, one-dimensional run-length coding (ODRLC) is one of the most commonly used approaches. T. S. Huang and others have found that the compression ratio of ODRLC can be improved by coding the black run-length (BRL) and the white run-length (WRL) separately. But

基于多波段预测的高光谱图像分布式无损压缩

提出了一种基于分布式信源编码的高光谱图像无损压缩算法,用于星载高光谱数据的有效压缩。为充分利用高光谱图像较强的谱间相关性,引入多波段谱间线性预测方案获取当前编码块的预测值,有效降低了编码块的最大预测残差值。在此基础上,根据最大预测残差值确定编码块各像素所属陪集的索引,通过传输每个像素所属陪集的索引代替预测残差,实现高光谱图像压缩。对星载可见/红外成像光谱仪(AVIRIS)获取的高光谱图像进行实验,并与已有的典型算法进行比较,结果显示该算法能够取得较好的无损压缩效果,同时具有较低的编码复杂度,适用于星载高光谱图像的无损压缩。

基于分类和陪集码的高光谱图像无损压缩

在基于陪集码的高光谱图像压缩算法中,由于按照编码块的最大残差确定整块无损压缩所需的码率存在较大冗余,该文提出了基于分类和陪集码的高光谱图像压缩算法。首先利用前一波段对应位置的预测噪声对当前波段编码块的像素进行分类,将具有相似相关性的像素归于一类,然后对每一类像素分别进行陪集码编码。实验表明分类可以有效地降低码率。和基于陪集码的算法相比,该文算法无损压缩的平均码率降低了大约0.4 bpp。

基于L_∞最小搜索和陪集码的高光谱图像无损及近无损压缩

分布式信源编码(DSC)由于其较低的编码复杂度及较高的抗误码性被应用于高光谱图像压缩.在典型的基于陪集码的分布式高光谱图像无损压缩算法s-DSC(scalar coset DSC)框架下,本文指出最优的预测准则应为无穷范数最小,提出了基于L∞最小搜索的预测方法来逼近最优准则,并将框架推广到近无损压缩.实验表明,和原有的s-DSC相比,本文算法无损压缩的平均码率降低了大约0.25bpp,近无损性能也明显优于JPEG-LS,本文算法具有较低的计算复杂度、较高的压缩性能,且具有一定的抗误码能力,适用于星上压缩.

基于图像平滑算法的电能质量数据压缩方法

为满足电能质量数据存储与传输的需要,基于图像平滑算法、二维离散小波变换以及图像多级树集合分裂编码算法提出了一种电能质量数据压缩新方法。将一维电能质量数据转换为二维矩阵以挖掘电能质量数据的循环间冗余性;应用数字图像平滑技术对二维变换后所得到的电能质量图像矩阵进行平滑处理以有利于二维小波变换编码;结合二维离散小波变换、图像多级树集合分裂编码以及DEFLATE编码算法对电能质量数据进行压缩。仿真实验结果表明,相对现有的电能质量数据压缩方法,所提出的方案不仅能更有效地压缩电能质量数据(同等压缩比的情况下,信噪比更高),而且还可以根据实际需求通过对压缩码率的控制灵活调节电能质量数据压缩性能。

基于分布式信源编码的高光谱图像无损压缩研究进展

有效的高光谱图像压缩技术已经成为航天高光谱遥感领域研究的焦点之一。对基于分布式信源编码(Distributed Source Coding,DSC)的高光谱图像压缩技术研究进展进行了综述。首先介绍了DSC的理论基础、实现方式及其在高光谱图像无损压缩应用中的优势;然后总结了基于DSC的高光谱图像无损压缩研究进展,在此基础上给出了一种基于多波段预测的高光谱图像分布式无损压缩算法,实验结果表明,该算法具有较低的编码复杂度,其无损压缩性能优于现有的分布式无损压缩算法;最后指出了DSC在高光谱图像压缩中需要进一步研究的问题。

数据压缩字典与快速图像分形映射压缩算法

针对分形编码压缩时间太长、以至于该算法很难达到实用的缺点 ,提出了对图像进行分级预处理 ,即根据被压缩图像的实际情况建立一个数据压缩字典 ,使得被压缩图像的匹配块仅在数据压缩字典指定的块中进行 ,从而大大减少图像压缩过程中的搜索范围和压缩时间·此外 ,给出了建立数据压缩字典的理论基础 ,并根据此思想给出了一个新的实现分形编码算法·实验表明 ,在提高压缩比的同时 。

运动补偿视频编码中DCT编码效率的研究

在视频序列图像编码中，运动补偿帧差图像的统计特性与静止自然图像有明显差别，对静止自然图像可以称为准最佳变换的离散余弦变换（ＤＣＴ）对帧差图像的编码效率有所下降。本文对这一问题进行了理论分析和实验验证，从而指出进一步提高视频序列图像编码效率的潜力所在。

似图形图像序列压缩编码方案的研究

针对远程炒股、远程教学和远程协同工作中的计算机屏幕共享问题 ,提出了一种对似图形图像序列进行无损压缩的编码方案。首先将似图形图像转化成索引图像 ,然后对索引图像序列进行帧间行程编码和自适应预测Huffman编码 ,最后再对码流进行LZ77编码。实验表明 ,该方案能够有效地压缩似图形图像序列 ,与一般的无损图像编码方案相比 ,明显地提高了图像的压缩效率 ,压缩比可达到 80∶1以上。

气象卫星云图数据的高效无失真压缩

在综合分析气象卫星云图数据高效无失真压缩方法的基础上，将二维ＤＰＣＭ预测器加反射型熵编码器用于各种灰度类型的气象卫星云图的无失真压缩，使压缩比与运算速度得到了较好的折中，实用效果较好．

匹配视觉生理机制的方向分解图象编码

本文对方向分解图像编码进行了系统研究。与Kunt方案相比,提出了更有效的边缘信息选择和编码算法,改进了内插方法和模型,并采用了新的方向滤波器设计方法,基于上述改进,建立了一套完整的匹配视觉生理机制的方向分解图像编码算法。系统模拟实验表明,当数据压缩比近60:1时,采用本方案仍能获得较好的图像质量。

嵌入式零树编码在天气雷达回波数据压缩中的应用

本文研究基于小波零树编码的天气雷达立体扫描数据压缩算法。根据雷达回波数据的特点 ,提出了一种有效的雷达数据预处理方案 ,然后利用Shapiro的嵌入式小波零树算法对预处理后的图像数据进行压缩实验。实验结果表明 ,该雷达回波数据压缩算法 ,在低比特率情况下 。