Volume 34 Issue 03
Mar.  2008
Turn off MathJax
Article Contents
Xiang Shiyong, Li Chunsheng, Chen Jieet al. Approach based on speckle reduction using SPIHT for data compression of complex SAR image[J]. Journal of Beijing University of Aeronautics and Astronautics, 2008, 34(03): 271-275. (in Chinese)
Citation: Xiang Shiyong, Li Chunsheng, Chen Jieet al. Approach based on speckle reduction using SPIHT for data compression of complex SAR image[J]. Journal of Beijing University of Aeronautics and Astronautics, 2008, 34(03): 271-275. (in Chinese)

Approach based on speckle reduction using SPIHT for data compression of complex SAR image

  • Received Date: 29 Jun 2007
  • Publish Date: 31 Mar 2008
  • A method based on speckle reduction using SPIHT(set partitioning in hierarchical trees) for data compression of complex SAR(synthetic aperture radar) image was presented, which could achieve both speckle reduction and image compression. According to the statistic characteristic of complex SAR image, complex SAR image was processed before wavelet transform. Soft-threshold speckle reduction and SPIHT image coding were applied to image compressing in wavelet domain. Wavelet coefficients in different subbands adopted different threshold in soft-threshold speckle reduction. The improved approach preserves the phase of the raw complex SAR image well and has a good effect of speckle reduction. It proves the efficiency of the improved approach for data compression of complex SAR image through evaluating phase error, ENL(equivalent number of looks) and complex spatial correlation efficient, comparing the intensity images of raw data and decompressed data, even at high compression ratio (64∶ 1).

     

  • loading
  • [1] 孙洪. 合成孔径雷达图像处理[M]. 北京:电子工业出版社,2005:58 Sun Hong. Image processing of synthetic aperture radar [M].Beijing: Publishing House of Electronics Industry,2005:58(in Chinese)  [2] Eichel P, Ives R W. Compression of complex-valued SAR images[J].IEEE Transactions Image Processing,1999,8 (10):1483-1487 [3] 张旭东,卢国栋,冯健.图像编码基础和小波压缩技术——原理、算法和标准[M].北京:清华大学出版社,2004:259-260 Zhang Xudong, Lu Guodong, Feng Jian. Image coding wavelet compression technology and the basis of: principles, algorithms and standards[M].Beijing:Tsinghua University Press,2004:259-260(in Chinese) [4] 孙明. 高分辨率SAR数据压缩算法研究 .北京:北京航空航天大学电子信息工程学院,2005 Sun Ming. Research on compression algorithms for high-resolution SAR data .Beijing: School of Electronic & Information Engineering, Beijing University of Aeronautics and Astronautics,2005(in Chinese) [5] Said A, Pearlman W A.New, fast, and efficient image codec based on set partitioning in hierarchical trees[J]. IEEE Trans Circuits Syst Video Techno, 1996,6(3):243-250 [6] Ives R W, Magotra N, Kiser C. Wavelet compression of complex SAR imagery using complex and real valued wavelets, a comparative study Conference Record of the Asilomar Conference on Signals, Systems & Computers. Los Alamitos, CA: IEEE Comp Soc,1998,2:1294-1298 [7] 燕英.合成孔径雷达斑点噪声理论分析与抑制方法研究 .北京航空航天大学电子信息工程学院,2002 Yan Ying. Analysis and reduction techniques of speckle in synthetic apterture radar images .Beijing: School of Electronic & Information Engineering, Beijing University of Aeronautics and Astronautics,2002(in Chinese) [8] 孙延奎.小波分析及其应用[M].北京:机械工业出版社,2005:139-142,233-235 Sun Yankui. Wavelet analysis and its application[M].Beijing: Machinery Industry Publishing House, 2005:139-142,233-235(in Chinese) [9] 谢海慧.SAR相干斑抑制及图像压缩的小波域方法 .成都:电子科技大学电子工程学院,2004 Xie Haihui.Speckle reduction and data compression in SAR images using wavelet-based method .Chengdu: Department of Electronic Engineering,University of Electronic Science and Technology,2004(in Chinese) [10] David D L.De-noising by soft-thresholding[J]. IEEE Transactions on Information Theory,1995,41(3):613-627 [11] 余越,薛永林,李凤亭,等.基于软门限去噪的图象压缩编码研究[J].中国图像图形学报,2001,6(1):46-50 Yu Yue, Xue Yonglin, Li Fengting, et al. Noise image coding using soft-threshold based denoising[J]. Journal of Image and Graphics, 2001,6(1):46-50(in Chinese)
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Article Metrics

    Article views(3428) PDF downloads(1222) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return