共查询到18条相似文献,搜索用时 62 毫秒
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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。 相似文献
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改进的快速SPIHT算法 总被引:8,自引:1,他引:7
SPIHT算法是一种简单、有效的嵌入式零树编码算法,但是,它需要大量存储空间,而且存在多次重复运算,因而复杂程度高,时间消耗大,不利于实时压缩。改进的SPIHT算法针对原算法的不足引入了“最小阈值”和“最小输出位”,同时改变了原算法的扫描顺序,降低了算法的复杂程度,并使其更有利于并行优化处理。实验证明,改进后的算法减少了编解码过程中的存储容量和时间消耗,而重建图像的峰值信噪比和人眼视觉效果与原算法相当。 相似文献
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由于SPIHT算法中存在的重复扫描和编码冗余,使得算法复杂度较高,工作效率较低.为了使算法更易于软、硬件的实现,通过调整小波系数矩阵的排序过程,使小波系数按从大到小排列,从而减少排序扫描的次数.实验表明,本算法在保持较高的信噪比的同时,仍具有较快的计算速度,明显的降低了处理复杂度,并节省了存储空间. 相似文献
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一种适于空间CCD图像压缩的SPIHT改进算法 总被引:2,自引:2,他引:0
针对传统遥感图像压缩多级树集合分裂排序(SP IHT)算法由于采用取决于图像内容的动态处理顺序而导致处理速 度缓慢这一问题,提出一种适于空间时间延时积分(TDI)CCD相机图像压缩的SPIHT改进算法 。首先,将小波变换后的图像分解成4×4块,同时对一个4×4块的 一个比特平面所有比特进行编码。为了实现并行处理机制,SPIHT改进算法重组传统SPIHT算 法的3个通道,然后采用并行和流水线作业的方式编码3个重组通道。实验结果表明,本文提 出的压缩算法可以稳定正常的 工作,具有良好压缩性能,平均信噪比(PSNR)性能与传统 方法相当,而数据吞吐率远高于传统方法。在正常100MHz时,数据 吞吐 率达到120Mpixle,大大提高压缩算法的处理速度。SPIHT改进算法 非常适合空间CCD相机图像压缩应用。 相似文献
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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。 相似文献
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分析了中子辐照图像的持点,提出一种适合于数字中子照相系统的图像压缩算法。将小波和方向滤波器组(DFB)结合,得到非冗余的图像变换WDFB;通过WDFB系数的重新组合,提出一种新颖的图像压缩方案,该方案类似于无表零树编码(LZC)算法;为了充分利用WDFB变换对二维分段光滑函数的良好表达能力,该算法引入线性索引技术并采用不同于LZC算法的零树表达策略。实验结果表明,该算法用于中子辐照图像压缩是有效的,在相同压缩比下,其主观视觉质量和峰值信噪比(PSNR)都明显优于LZC算法,和多级树集合分裂编码(SPIHT)算法相比,具有相当的压缩性能但更易于硬件实现。 相似文献
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改进的图像多分辨率零树小波编码算法 总被引:8,自引:1,他引:8
本文在研究Shapiro零树方法进行小波图像编码基础上,提出一种改进型多分辨率零树编码算法。本算法从客观信噪比的角度出发,以码流中增加单位码字平均所能减少的系数量化误差为依据,确定各部分小波系数参加编码的顺序,同等码率下可提高PSNR0.1~0.5dB,同时改进后的算法可以使编码产生的码流在原来支持多码率解码的基础上,支持多分辨率图像解码 相似文献
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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. 相似文献
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本文提出了等级树集合分区算法(SPIHT)的一种改进方案,对图像的小波变换域的三个空间方向(水平、垂直和对角)上的系数构成等级树型结构,并对各空间方向等级树单独进行编码,使得在不影响恢复图像质量的情况下,进一步提高压缩比.仿真实验表明了本算法的有效性. 相似文献
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A fast and low memory image coding algorithm based on lifting wavelet transform and modified SPIHT 总被引:1,自引:0,他引:1
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. 相似文献
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Ranjan K. Senapati Umesh C. Pati Kamala Kanta Mahapatra 《AEUE-International Journal of Electronics and Communications》2012,66(12):985-995
This paper presents a listless implementation of wavelet based block tree coding (WBTC) algorithm of varying root block sizes. WBTC algorithm improves the image compression performance of set partitioning in hierarchical trees (SPIHT) at lower rates by efficiently encoding both inter and intra scale correlation using block trees. Though WBTC lowers the memory requirement by using block trees compared to SPIHT, it makes use of three ordered auxiliary lists. This feature makes WBTC undesirable for hardware implementation; as it needs a lot of memory management when the list nodes grow exponentially on each pass. The proposed listless implementation of WBTC algorithm uses special markers instead of lists. This reduces dynamic memory requirement by 88% with respect to WBTC and 89% with respect to SPIHT. The proposed algorithm is combined with discrete cosine transform (DCT) and discrete wavelet transform (DWT) to show its superiority over DCT and DWT based embedded coders, including JPEG 2000 at lower rates. The compression performance on most of the standard test images is nearly same as WBTC, and outperforms SPIHT by a wide margin particularly at lower bit rates. 相似文献
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本文提出了采用树结构矢量组合对小波图像进行分类矢量量化的新方法.该方法充分利用了子带系数的带间和带内的相关性,分类信息占用比特数少,并采用了基于人眼视觉特性的加权均方误差准则进行矢量量化,提高了量化增益.仿真结果表明,该方法实现简单,可达到很好的压缩效果. 相似文献
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该文针对多极化合成孔径雷达(SAR)图像在极化通道之间的相关性,提出了3D-SPIHT压缩方法。将多极化SAR图像(HH,HV,VV图像)作为一个整体,进行三维矩阵变换。首先在极化通道之间进行一维DCT变换,极化平面内进行二维离散小波变换(DWT),然后对3个极化混合系数平面采用分级树的集合划分(SPIHT)算法进行嵌入式统一混合编码。由于不是单独处理每一极化图像,因此不仅可以去除各极化图像内部之间的相关性,也可以去除极化通道之间的相关性。另外,由于采用统一嵌入编码,码流具有完全嵌入性,可以实现3个极化平面之间比特的精确自动分配。理论推导和仿真结果表明该方法对多极化SAR图像压缩是十分有效的。 相似文献