In this paper, we focus on a high performance compression scheme for remote-sensing images, which is essential due to limited transmission bandwidth while explosively growing remote-sensing image data size. First, on the basis of intra-image spatial redundancy removal, which is used by JPEG 2000 and CCSDS, priori-information is introduced to eliminate temporal redundancy between historical and newly-captured images, at the same time. Second, feature registration technique is applied rather than motion estimation and compensation which is used in HEVC, to deal with the long-range non-linear correlation of remote-sensing image series. Numerical simulation results show that the proposed scheme outperforms JPEG 2000 and JPEG by over 1.37 times for lossless compression, and presents a 5 dB PSNR gain over JPEG 2000 and HEVC for lossy compression.


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    Titel :

    Remote-Sensing Image Compression Using Priori-Information and Feature Registration


    Beteiligte:
    Liu, XiJia (Autor:in) / Tao, XiaoMing (Autor:in) / Ge, Ning (Autor:in)


    Erscheinungsdatum :

    01.09.2015


    Format / Umfang :

    321970 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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