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Interferential Multi-spectral Image Compression Based on Distributed Source Coding

机译:基于分布式源编码的干涉多光谱图像压缩

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Based on the analyses of the interferential multispectral imagery(lMI), a new compression algorithm based on distributed source coding is proposed. There are apparent push motions between the IMI sequences, the relative shift between two images is detected by the block match algorithm at the encoder. Our algorithm estimates the rate of each bitplane with the estimated side information frame, then our algorithm adopts a ROI coding algorithm, in which the rate-distortion lifting procedure is carried out in rate allocation stage. Using our algorithm, the FBC can be removed from the traditional scheme. The compression algorithm developed in the paper can obtain up to 3dB's gain comparing with JPEG2000 and significantly reduce the complexity and storage consumption comparing with 3D-SPIHT at the cost of slight degrade in PSNR.
机译:在分析干涉多光谱图像的基础上,提出了一种基于分布式源编码的压缩算法。 IMI序列之间存在明显的推动运动,两个图像之间的相对偏移由编码器处的块匹配算法检测到。我们的算法利用估计的辅助信息帧估计每个位平面的速率,然后我们的算法采用ROI编码算法,其中在速率分配阶段执行速率失真提升程序。使用我们的算法,FBC可以从传统方案中删除。本文开发的压缩算法与JPEG2000相比,可获得高达3dB的增益,与3D-SPIHT相比,可以显着降低复杂度和存储消耗,但代价是PSNR会略有下降。

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