期刊文献+

一种简单误码检错多分辨率SPIHT算法 被引量:1

New multi-resolution SPIHT approach with simple error detection
下载PDF
导出
摘要 由EZW算法演变而来的SPIHT算法是目前为止影响最大的小波压缩算法之一,它通过独特的扫描方式,将小波系数按照能量大小或者重要性程度编码输出。由于引入了小波树,隐藏了扫描路径,SPIHT能获得高压缩比,同时保持较高的图像质量。而后提出的多分辨率SPIHT算法能使解码器根据信道条件,选择图像还原分辨率。然而,SPIHT对路径可靠性要求严苛,任何路径信息的传输错误都会导致剩余所有码元的解码出错。许多学者就路径码元的保护提出了不同改进,却未能从根本上提高算法的抗噪性能。为此,提出了一种改进了的SPIHT算法,该算法在保持较高信噪比和不增加码元数量的基础上,使解码器具有简单误码检错能力。 SPIHT algorithm, evolving from EZW, is so far one of the most influential wavelet compression algorithms, which encodes wavelet coefficients according to their energy or significance through a unique pass. Due to the introduction of wavelet tree and the certain pass, high compression ratio was obtained as well as high quality of image or video. Multi-resolution SPIHT, being later proposed, promised resolution option based on channel condition. However, accurate path information is so demanded in SPIHT that any error of path bit will bring decoding failure of following bits. Various mechanisms were employed to protect the path information, which turn out of little help to fundamentally enhance its capability of anti-noise. The algorithm proposed in the paper provides the decoder with high PSNR and error detection without additional bits by improving the original algorithm.
出处 《计算机应用》 CSCD 北大核心 2007年第4期972-975,共4页 journal of Computer Applications
基金 国家自然科学基金资助项目(60502016) 上海市科委专项基金资助项目(05dz12006) 同济大学工科发展基金资助项目(0800219040)
关键词 图像压缩 分级树集合划分 多分辨率 检错 image compression Set Partitioning in Hierarchical Trees (SPIHT) multi-resolution error detection
  • 相关文献

参考文献10

二级参考文献24

  • 1[1]Said A, Pearlman W. A new, fast, and efficient image codec based on set partitioning in hierarchical trees [J]. IEEE Transactions on Circuits and Systems for Video Technology, 1996, 6(3): 243250.
  • 2[2]Shapiro J. Embedded image coding using zerotrees of wavelets coefficients [J]. IEEE Transactions on Signal Processing, 1993, 41(12): 34453462.
  • 3[3]Antonini M, Barlaud M, Mathieu P, et al. Image coding using wavelet transform [J]. IEEE Transactions on Image Processing, 1992, 1(2): 205220.
  • 4M. MASLEN,P. ABBOTT. Automation of the lifting factorization of wavelet transforms [J]. Computer Physics Communications,2000,127:309-326.
  • 5Amir Z. AVERBUCH,Valery A. ZHELUDEV. Lifting scheme for biorthogonal mutiwavelets originated from hermite splines [J]. IEEE Trans. Signal Processing,2002,50(3):487-500.
  • 6Rafael C. GONZALEZ,Richard E. WOODS. Digital image processing: second ed [M]. Beijing:Publishing House of Electronics Industry,2002.
  • 7Marc ANTONINI,Michel BARLAUD,Pierre MATHIEU,et al. Image coding using wavelet transform [J]. IEEE Trans. Image Processing,1992,1(2):205-220.
  • 8J. M. SHAPIRO. Embedded image coding using zerotree of wavelets coefficients [J]. IEEE Trans. Signal Processing,1993,41(12):3445-3462.
  • 9Amir SAID,William A.PEARLMAN .A new,fast,and efficient image codec based on set partitioning in hierarchical trees [J]. IEEE Transactions On Circuits and Systems for Video Technology,1996,6(3):243-250.
  • 10SAID A,PEARLMAN WA.A New Fast and Efficient Image Code Based on Set Partitioning in Hierarchical Trees[J].IEEE Transactions on Circuits and Systems for Video Technology,1996,6(3):243-250.

共引文献55

同被引文献7

引证文献1

二级引证文献3

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部