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。     

基于多小波域新型空间方向树的SPIHT改进算法

为了更好地利用图像多小波域系数的相似性进行编码,提出了一种基于多小波域新型空间方向树的SPIHT改进算法。在SPIHT改进算法中首先定义了一种新型空间方向树把多小波域中不同子带的相似系数和每个子带中各个子块的相似系数组织在一起,然后根据树的结构改进了算法中分裂排序过程。实验结果表明,SPIHT改进算法与原来的SPIHT算法相比,在相同的压缩比下可以获得更高的峰值信噪比。     

一种球坐标系下小波收缩去噪新算法

基于Besov空间范数理论提出一个新的球坐标下的自适应收缩阈值,并将小波域上的多尺度积推广到球坐标下,充分利用尺度间小波系数的相关性。最后,提出了一种新的自适应曲线收缩函数,此函数有一定的边缘增强效果。根据球坐标下图像的统计特性,用新的收缩阈值和新的收缩函数进行去噪处理。仿真实验分别从峰值信噪比(PSNR)、均方误差(MSE)和运行时间上进行评估,确立了最佳分解尺度,并且与其它算法相比,提高了PSNR,而且具有运算简单、运算量小的优点。     

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.     

适于航天应用的高速SPIHT图像压缩算法

SPIHT和无链表SPIHT(Not List SPIHT)是高效的图像压缩算法,但是抗误码性差、压缩速度慢等缺点限制了其在航天领域的应用。文章针对上述两个缺点对算法进行了改进,采用Le Gall5/3小波对遥感图像进行小波分解,将小波域系数分家族块进行索引、扫描和码率分配,按照比特平面或运算进行重要性预测,实现了N个位平面同时编码。改进算法与SPIHT相比易于硬件编程实现,仿真结果显示,解压后图像峰值信噪比(PSNR)提高了0.2～0.6db,压缩速度提高了4～6倍。用硬件实现时如果采用并行和流水线操作,速度还可以进一步提高。     

基于球坐标的非线性小波变换图像压缩编码算法

利用小波变换的3个高频分量之间相关特性,提出了基于球坐标变换的非线性小波变换图像压缩编码的方法,在小波收缩中,采用双曲线收缩处理球坐标下的径向分量以提高重建图像的质量,实验结果表明,此算法在压缩比和重建质量方面都取得较好的效果。     

基于球坐标的非线性小波变换图像压缩编码算法

利用小波变换的3个高频分量之间相关特性,提出了基于球坐标变换的非线性小波变换图像压缩编码的方法.在小波收缩中,采用双曲线收缩处理球坐标下的径向分量以提高重建图像的质量.实验结果表明此算法在压缩比和重建质量方面都取得较好的效果.     

改进SPIHT算法对医学图像的压缩

医学图像是医学诊断和疾病治疗的重要根据。为了实现图像的存储和远程医疗中快速传输图像的要求,必须对图像进行压缩。先分析CT医学图像经过小波变换后系数的统计特性,在基于小波变换的基础上,用SPIHT算法对CT医学图像进行压缩编码。提出了2种针对CT医学图像压缩编码改进的SPIHT算法。一是细化扫描产生的有效值,二是将小波变换后系数的低频近似部分按二进比特进行传输。用Matlab进行仿真,仿真结果表明改善了峰值信噪比。     

基于3维SPIHT编码的超光谱图像压缩

提出一种针对超光谱图像压缩的3维SPIHT编码算法.通过对超光谱图像进行3维小波变换,同时去除像素数据间的空间冗余和谱间冗余.针对变换后得到的小波系数,构造一种3维空间方向树结构,并用经3维扩展后的SPIHT算法(3D SPIHT算法)对小波系数进行量化编码.实验证明,基于3维小波变换的3维SPIHT编码算法在对超光谱图像压缩时,表现出了优良的率失真性能.并且算法复杂度适中,具有嵌入式特性.     

改进的小波域三维等级树集分割视频编码方法

本文主要研究了视频图像在小波域进行压缩的三维等级树集分割编码（3D－SPIHT）方法,提出了一种改进的三维等级树集分割编码方法（13D－SPIHT）,该方法克服了3D－SPIHT的限制。通过分析和仿真实验发现,本文的改进算法在降低编码延迟的基本下基本上能达到和3D－SPIHT方法相同的编码结果,在相同的编码时延的条件下可得到更好的编码结果。     

一种基于低复杂度嵌入零块编码的遥感图像压缩编码方法

该文针对遥感图像的数据特点,提出了一种新的遥感图像编码方法。它基于一种改进的小波变换嵌入零块编码算法。新算法中改进了零块编码中四叉树分裂算法(quadtree),并设计亍新的链表生成和不重要集合排序策略。通过这些方法的改进,不仅提高了图像编码性能,同时还大大提高了运算效率。实验表明该文阐述的算法具有很低的复杂度和高的压缩率,PSNR和计算速度均超过SPIHT和SPECK。在1bpp下,该文方法的PSNR比SPIHT提高了0.3dB以上,计算速度比SPIHT提高了35％。     

A COMPRESSION ALGORITHM FOR ECG BASED ON INTEGER LIFTING SCHEME WAVELET TRANSFORM

In view of the shortcomes of conventional ElectroCardioGram (ECG) compression algo- rithms,such as high complexity of operation and distortion of reconstructed signal,a new ECG compression encoding algorithm based on Set Partitioning In Hierarchical Trees (SPIHT) is brought out after studying the integer lifting scheme wavelet transform in detail.The proposed algorithm modifies zero-tree structure of SPIHT,establishes single dimensional wavelet coefficient tree of ECG signals and enhances the efficiency of SPIHT-encoding by distributing bits rationally,improving zero-tree set and ameliorating classifying method.For this improved algorithm,floating-point com- putation and storage are left out of consideration and it is easy to be implemented by hardware and software.Experimental results prove that the new algorithm has admirable features of low complexity, high speed and good performance in signal reconstruction.High compression ratio is obtained with high signal fidelity as well.     

基于小波图像编码算法的改进及实现

针对现有SPIHT算法存在的不足,提出了一种新的改进编码方案。该算法通过引入图像平滑预处理和边缘检测,很好地提高了图像视觉效果和重构图像的PSNR值,并且进一步改进了编码传输策略,对最低频子带单独进行编码,对高频子带采用无链表SPIHT算法。实验结果表明:该算法有效地克服了SPIHT算法存在的不足,其编码速度和图像恢复质量,均优于SPIHT算法(特别是对纹理丰富的图像)。     

一种基于标准Walsh变换的改进SPIHT算法

在图像压缩领域,SPIHT被认为是目前最先进的嵌入式零树编码方法之一。利用SPIHT编码算法的优越性,结合Walsh变换的能够将矩阵能量向矩阵左上角集中的特点,提出了一种基于标准Walsh变换的改进SPIHT算法。仿真试验结果表明,在压缩比相同的情况下,算法的信噪比明显高于SPIHT算法信噪比。     

三维小波变换结合运动补偿的视频编码器

对三雏小波变换结合运动补偿的视频压缩算法提出了改进方案。针对运动补偿提升（MCLIFT）框架的弱点，结合MPEG的特点，采用新的帧结构对视频序列进行帧间滤波去除时间冗余，再对每个帧在空间上进行小波分解并用SPIHT算法对小波系数进行编码。实验表明，此方法继承了MCLIFT框架的优点，同时又减少了时延和所需的帧缓存，而且这种与MPEG相似的帧结构能进一步降低码率，提高压缩比。     

A 2-D ECG compression method based on wavelet transform and modified SPIHT

A two-dimensional (2-D) wavelet-based electrocardiogram (ECG) data compression method is presented which employs a modified set partitioning in hierarchical trees (SPIHT) algorithm. This modified SPIHT algorithm utilizes further the redundancy among medium- and high-frequency subbands of the wavelet coefficients and the proposed 2-D approach utilizes the fact that ECG signals generally show redundancy between adjacent beats and between adjacent samples. An ECG signal is cut and aligned to form a 2-D data array, and then 2-D wavelet transform and the modified SPIHT can be applied. Records selected from the MIT-BIH arrhythmia database are tested. The experimental results show that the proposed method achieves high compression ratio with relatively low distortion and is effective for various kinds of ECG morphologies.     

Motion compensated lossy-to-lossless compression of 4-D medical images using integer wavelet transforms.

This paper proposes a method for progressive lossy-to-lossless compression of four-dimensional (4-D) medical images (sequences of volumetric images over time) by using a combination of three-dimensional (3-D) integer wavelet transform (IWT) and 3-D motion compensation. A 3-D extension of the set-partitioning in hierarchical trees (SPIHT) algorithm is employed for coding the wavelet coefficients. To effectively exploit the redundancy between consecutive 3-D images, the concepts of key and residual frames from video coding is used. A fast 3-D cube matching algorithm is employed to do motion estimation. The key and the residual volumes are then coded using 3-D IWT and the modified 3-D SPIHT. The experimental results presented in this paper show that our proposed compression scheme achieves better lossy and lossless compression performance on 4-D medical images when compared with JPEG-2000 and volumetric compression based on 3-D SPIHT.     

A fast and low memory image coding algorithm based on lifting wavelet transform and modified SPIHT

Due to its excellent rate–distortion performance, set partitioning in hierarchical trees (SPIHT) has become the state-of-the-art algorithm for image compression. However, the algorithm does not fully provide the desired features of progressive transmission, spatial scalability and optimal visual quality, at very low bit rate coding. Furthermore, the use of three linked lists for recording the coordinates of wavelet coefficients and tree sets during the coding process becomes the bottleneck of a fast implementation of the SPIHT. In this paper, we propose a listless modified SPIHT (LMSPIHT) approach, which is a fast and low memory image coding algorithm based on the lifting wavelet transform. The LMSPIHT jointly considers the advantages of progressive transmission, spatial scalability, and incorporates human visual system (HVS) characteristics in the coding scheme; thus it outperforms the traditional SPIHT algorithm at low bit rate coding. Compared with the SPIHT algorithm, LMSPIHT provides a better compression performance and a superior perceptual performance with low coding complexity. The compression efficiency of LMSPIHT comes from three aspects. The lifting scheme lowers the number of arithmetic operations of the wavelet transform. Moreover, a significance reordering of the modified SPIHT ensures that it codes more significant information belonging to the lower frequency bands earlier in the bit stream than that of the SPIHT to better exploit the energy compaction of the wavelet coefficients. HVS characteristics are employed to improve the perceptual quality of the compressed image by placing more coding artifacts in the less visually significant regions of the image. Finally, a listless implementation structure further reduces the amount of memory and improves the speed of compression by more than 51% for a 512×512 image, as compared with that of the SPIHT algorithm.