卫星遥感图像无损压缩技术改进方法
|
摘要
采用预测原理的JPEG-LS无损压缩算法存在着固有的误码扩散现象,会影响其在卫星工程中的应用,且基于整幅图像预测的压缩算法还存在较大的处理时延,难以满足遥感图像实时性应用需求。文章对JPEG-LS无损压缩算法进行了改进,提出了采取分块压缩的措施来抑制误码扩散同时降低图像处理时延的方法,并利用风云四号(FY-4)卫星扫描图像对改进的JPEG-LS无损压缩算法进行了验证。结果表明:改进的JPEG-LS无损压缩算法可在有效抑制误码扩散的条件下,实时无损地将卫星遥感图像数据量压缩至一半左右。可为卫星遥感图像无损压缩技术的改进及工程应用提供参考。
The JPEG-LS image lossless compression algorithm based on the theory of predict has the error-bit propagation effect,which restricts its engineering application,and the delay caused by the total frame image compression will not satisfy the real-time requirement.Therefore the method of the small piece image compression is proposed used to improve JPEG-LS,which is tested using the remote sensing image of FY-4 satellite.The results show that the improved JPEG-LS lossless image compression algorithm can suppress the error-bit propagation as well as real-time and lossless half reduced the data transmitted to the earth.This paper can provide reference on the satellite remote sensing image lossless compression technology improved and engineering application.
The JPEG-LS image lossless compression algorithm based on the theory of predict has the error-bit propagation effect,which restricts its engineering application,and the delay caused by the total frame image compression will not satisfy the real-time requirement.Therefore the method of the small piece image compression is proposed used to improve JPEG-LS,which is tested using the remote sensing image of FY-4 satellite.The results show that the improved JPEG-LS lossless image compression algorithm can suppress the error-bit propagation as well as real-time and lossless half reduced the data transmitted to the earth.This paper can provide reference on the satellite remote sensing image lossless compression technology improved and engineering application.
引文
[1]杜列波.星载遥感图像JPEG2000压缩算法的去量化[D].长沙:国防科技大学,2009DuLiebo.Quantification removing for satellite on-board remote image JPEG2000 compression algorithm[D].Changsha:National University of Defense Technolog,2009(in Chinese)
[2]姜波.多通道卫星云图的图像处理技术研究[D].哈尔滨:哈尔滨工程大学,2012Jiang Bo.Image processing technology of multi-channel data of satellite cloud image[D].Harbin:Harbin Engineering University,2012(in Chinese)
[3]CCSDS.Lossless Data Compression green book.Recommendation for space data system standards,CCSDS121.0-G-2[R].Washington D.C.:CCSDS,2006:16-24
[4]胡栋.静止图像编码的基本方法与国际标准[M].北京:北京邮电大学出版社,2003Hu Dong.The basic methods and the international stand of static image compress[M].Beijing:Beiyou University Press,2003(in Chinese)
[5]Aaron Kiely,Roberto Manduchi,Matthem Klimesh.Maximizing science return:Data compression and onboard science processing[M].Germany:Springer,2000:12-13
[6]Marcelo J,Weinberger.The LOCO-I lossless image compression algorithm[J].IEEE Transactions on Image Processing,2000,9(8):2-5
[7]David S Taubman,Michael W Marcellin.The basic methods,stand and usage of JPEG2000image compress[M].Beijing:Publishing House of Electronics Industry,2004
[8]冯希.几种图像无损压缩与编码方法研究[D].西安:中国科学院西安光学精密机械研究所,2008Feng Xi.Comparison of several lossless image compression and coding algorithms[D].Xi’an:Chinese Academy of Sciences,Xi’an Institute of Optical Precision Mechanism,2008(in Chinese)
[9]许贵.星载遥感图像压缩中的变换算法研究[D].南京:南京理工大学,2009Xu Gui.The study on transform algorithm of the satellite remote sensing image compression[D].Nanjing:Nanjing University of Science and Technology,2009(in Chinese)
[10]龚燃.美国下一代静止气象卫星[J].国际太空,2013(9):20Gong Ran.The next generation meteorological satellite of the United Sates[J].Space International,2013(9):20(in Chinese)
[2]姜波.多通道卫星云图的图像处理技术研究[D].哈尔滨:哈尔滨工程大学,2012Jiang Bo.Image processing technology of multi-channel data of satellite cloud image[D].Harbin:Harbin Engineering University,2012(in Chinese)
[3]CCSDS.Lossless Data Compression green book.Recommendation for space data system standards,CCSDS121.0-G-2[R].Washington D.C.:CCSDS,2006:16-24
[4]胡栋.静止图像编码的基本方法与国际标准[M].北京:北京邮电大学出版社,2003Hu Dong.The basic methods and the international stand of static image compress[M].Beijing:Beiyou University Press,2003(in Chinese)
[5]Aaron Kiely,Roberto Manduchi,Matthem Klimesh.Maximizing science return:Data compression and onboard science processing[M].Germany:Springer,2000:12-13
[6]Marcelo J,Weinberger.The LOCO-I lossless image compression algorithm[J].IEEE Transactions on Image Processing,2000,9(8):2-5
[7]David S Taubman,Michael W Marcellin.The basic methods,stand and usage of JPEG2000image compress[M].Beijing:Publishing House of Electronics Industry,2004
[8]冯希.几种图像无损压缩与编码方法研究[D].西安:中国科学院西安光学精密机械研究所,2008Feng Xi.Comparison of several lossless image compression and coding algorithms[D].Xi’an:Chinese Academy of Sciences,Xi’an Institute of Optical Precision Mechanism,2008(in Chinese)
[9]许贵.星载遥感图像压缩中的变换算法研究[D].南京:南京理工大学,2009Xu Gui.The study on transform algorithm of the satellite remote sensing image compression[D].Nanjing:Nanjing University of Science and Technology,2009(in Chinese)
[10]龚燃.美国下一代静止气象卫星[J].国际太空,2013(9):20Gong Ran.The next generation meteorological satellite of the United Sates[J].Space International,2013(9):20(in Chinese)