一种基于Contourlet的无表零树图像编码算法

该文提出一种低存储量、高压缩性能的基于Contourlet变换的无表零树编码算法。通过对Contourlet系数的重新组合,该算法采用类似LZC的零树结构;为了充分利用Contourlet变换对二维分段光滑函数的良好表达能力,设计了不同于LZC 算法的扫描顺序和标志图表示,降低了编解码复杂度。实验结果表明,该算法用于图像编码是有效的,在相同压缩比下,其主观视觉质量和PSNR都明显优于基于小波变换的LZC和SPIHT算法,尤其对于含有丰富纹理的图像。     

基于整数提升小波变换的彩色图像零树编码算法

提出了一种易于硬件实现的低存储量，高压缩性能的基于整数提升小波变换的彩色图像无链表SPIHT零树编码算法，该算法采用了一种低频子带优先的线性指针扫描顺序和不同于Wen-Kuo Lin提出的无链表LZC算法的状态比特表及零树分割策略，实验结果表明作者提出的算法在性能上（PSNR）比LZC高约0．5dB左右，和SPIHT算法相比具有同样的压缩性能，但更易于硬件实现。     

EZW算法在DICOM图像压缩中的研究

基于小波变换的图像编码是一种有效的图像压缩方法，近几年来得到了广泛的发展，其中最著名的是Shapiro提出的小波零树编码（EZW）方法。针对医学DICOM图像的需求和特点，本文提出了一种基于小波变换的EZW算法对DICOM图像进行压缩。     

一种基于高频子带的有序四叉树图像编码算法

在分析小波变换后系数特点和零树编码算法的基础上，提出了一种新的算法。主要思想是：设立位置矩阵记录子带的位置信息。对高频子带内小波系数进行扫描排序形成有序四叉树，对输出的符号串采取行程编码。理论分析和实验结果表明：该算法能加快编码速度，提高了图像压缩的质量。     

一种改进的无表零树编码的图像压缩方法

本文对SPIHT算法进行了改进,得到一种在编码和解码过程中都不用链表的小波零树编码方法,称为改进的无表零树编码.这种编码方法大大地减少了内存消耗,降低了编码复杂度,提高了编码速度.实验表明,在相同压缩比下本文算法比LZC算法提高了0.66dB,因此为硬件实现图像压缩编码提供了一种有效的方法.     

一种改进的零树结构编码算法研究

现在大部分图像压缩技术都利用了小波变换后图像不同分辨率反相同方向子带之间的相关性。采用双正交提升小波将图像变换到小波域,通过增加熵编码的符号集,提出了一种基于正交小波变换的增广零树压缩编码算法,在整个编译码过程中仅使用一个系数列表,况且不进行任何排序操作。通过相关实验,证实该方法能有效进行图像压缩,提高了压缩率。     

一种改进的基于小波变换的快速EZW算法

研究了一种适合在高速DSP上运行的基于小波变换的快速嵌入式零树编码（EZW）算法。通过分析传统EZW的数据压缩流程以及DSP的处理机制,对EZW算法进行了改进,使之在DSP上运行的速度得到了极大的提高,并已在某高输入数据率的图像压缩项目上使用,效果良好。     

一种基于小波系数重要图编码的图像压缩算法

提出了一种新的基于小波系数重要图编码的图像压缩算法。该算法根据量化后的波系数的特点进行了一种期望排序，然后舍掉序列后面大量的零值小波系数，从而得到一个波系数子集，能以少的小波系数来很好地逼近原始图像，省去了零树编码中零树结构带来的大量比特开销。实验表明，该算法与MPEG-4的静止图像压缩算法相比较，重构图像的峰值信噪比（PSNR）值在相同码率下有较大的提高。     

小波变换编码及其在军事图像上的应用

提出了一种军事图像压缩的新方法,在嵌入式零树小波(EZW)算法基础上引入提升方案和整数变换以降低算法复杂度,在编码前对系数按重要性进行排序并对低频区域的系数的符号进行改变.实验结果表明,将该算法用于军事图像压缩无论在主观效果还是在峰值信噪比方面都取得了满意的效果.     

零树编码在图像压缩中的应用

零树编码是基于小波变换的一种图像压缩方式,它的出现为实现高压缩比、高质量压缩图像提供了新途径。近几年,随着矢量量化技术的广泛应用,零树编码思想再次被赋予新的活力。针对零树编码思想在图像压缩领域中的应用进行缩合性的描述。     

Image coding using lapped biorthogonal transform

The wireless sensor network utilizes image compression algorithms like JPEG, JPEG2000, and SPIHT for image transmission with high coding efficiency. During compression, discrete cosine transform (DCT)–based JPEG has blocking artifacts at low bit-rates. But this effect is reduced by discrete wavelet transform (DWT)–based JPEG2000 and SPIHT algorithm but it possess high computational complexity. This paper proposes an efficient lapped biorthogonal transform (LBT)–based low-complexity zerotree codec (LZC), an entropy coder for image coding algorithm to achieve high compression. The LBT-LZC algorithm yields high compression, better visual quality with low computational complexity. The performance of the proposed method is compared with other popular coding schemes based on LBT, DCT and wavelet transforms. The simulation results reveal that the proposed algorithm reduces the blocking artifacts and achieves high compression. Besides, it is analyzed for noise resilience.     

基于DCT变换的内嵌静止图像压缩算法

提出了一种有效的基于离散余弦变换(DCT)的内嵌子带图像编码算法.Xiong等人提出的EZDCT算法采用零树结构实现了一种内嵌DCT编码器,且其性能优于JPEG.本文指出DCT的零树结构在内嵌DCT算法中并非很有效,同时提出了一种不依赖零树结构的简便、高效的内嵌DCT子带编码算法.实验结果表明本文算的压缩性能(PSNR)比EZDCT高约0.5~1.5dB,且接近当前最通用的内嵌小波SPIHT算法,在对某些图像压缩时还优于SPIHT算法.     

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。     

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.     

A low memory zerotree coding for arbitrarily shaped objects

The set partitioning in hierarchical trees (SPIHT) algorithm is a computationally simple and efficient zerotree coding technique for image compression. However, the high working memory requirement is its main drawback for hardware realization. We present a low memory zerotree coder (LMZC), which requires much less working memory than SPIHT. The LMZC coding algorithm abandons the use of lists, defines a different tree structure, and merges the sorting pass and the refinement pass together. The main techniques of LMZC are the recursive programming and a top-bit scheme (TBS). In TBS, the top bits of transformed coefficients are used to store the coding status of coefficients instead of the lists used in SPIHT. In order to achieve high coding efficiency, shape-adaptive discrete wavelet transforms are used to transformation arbitrarily shaped objects. A compact emplacement of the transformed coefficients is also proposed to further reduce working memory. The LMZC carefully treats "don't care" nodes in the wavelet tree and does not use bits to code such nodes. Comparison of LMZC with SPIHT shows that for coding a 768 /spl times/ 512 color image, LMZC saves at least 5.3 MBytes of memory but only increases a little execution time and reduces minor peak signal-to noise ratio (PSNR) values, thereby making it highly promising for some memory limited applications.     

Low-bit-rate coding of underwater color image using improved wavelet difference reduction

Underwater image compression has been the key technology for transmitting massive amount of image data via underwater acoustic channel with limited bandwidth. According to the characteristics of underwater color images, an efficient underwater image compression method has been developed. The new coding scheme employs a wavelet-based preprocessing method to remove the visual redundancy, and adopts a Wavelet Tree-based Wavelet Difference Reduction (WTWDR) algorithm to remove the spatial redundancy of underwater color images. Instead of scanning whole transformed image like the WDR method, the difference reduction coding is used for each significant wavelet tree in the proposed WTWDR algorithm based on the correlation between the subbands of higher levels and lower levels of a transformed image. The experimental results show that for underwater color images the proposed method outperforms both WDR and SPIHT at very low bit rates in terms of compression ratio and reconstructed quality, while for natural images it has similar performance with WDR and SPIHT. Hence, the proposed approach is especially suitable for underwater color image compression at very low bit rates.     

改进的SPIHT算法

SPIHT算法是一种高效的嵌入式的零树编码算法,然而,它需要大量的内存空间,不利于DSP或VLSI的实现。LZC算法可以极大地降低编解码器的内存需求,但同时也降低了编解码器的性能。该文利用LZC算法的思想,改进了原来的SPIHT算法,使得在仅仅在LZC算法的内存需求基础上,达到SPIHT算法的性能要求。同时又提出了一种近似搜索算法来提高编码器的速度。     

Zerotree pattern coding of motion picture residues forerror-resilient transmission of video sequences

This paper describes a compression scheme for difference-image residues in video coding. Structured spatial patterns are used to map residue pixel values into a quadtree structure, which is then coded in significance order with the SPIHT algorithm. Thus the wavelet coefficient values of standard zerotree coding are replaced by untransformed (but carefully positioned) residue pixel values. The new zerotree pattern coding method compresses as well as zerotree wavelet coding and much better than DCT coding (as in MPEG) over error-free channels. Over noisy channels, zerotree pattern coding provides built-in error resilience, allowing transmission of residue data without error control overhead. A simple postprocessing technique provides additional error concealment