基于V型扫描的星载多光谱图像无损压缩算法

为了实现星载多光谱图像的无损压缩,深入研究了空间数据系统咨询委员会(CCSDS)建议的123.0-B-1标准;并结合CCD多光谱遥感成像特点,提出了利用V型扫描对预测方式进行改进;最后在VC6.0平台下实现了该算法。实验结果表明,该算法的平均压缩率比Z型扫描方式的CCSDS 123.0-B-1、CCSDS 121.0-B-1、CCSDS 122.0-B-1、JPEG-LS标准算法的平均压缩率分别高6.7%、68.9%、21.8%和12.9%。该算法复杂度低,适合运用于星上系统。

Space-based multispectral image lossless compression algorithm based on V-scan

In order to implement lossless compression of space-based multispectral images, the 123.0-B-1standard recommended by Consultative Committee for Space Data System Standards (CCSDS) was studied , and an idea of using V-scan was presented to improve the prediction method combining with the characteristics of CCD multispectral remote sensing imaging. The algorithm was implemented on the VC6.0 platform. The experimental results indicate that on the average the compression ratio using this algorithm increases by 6.7%, 68.9%, 21.8% and 12.9% compared to CCSDS 123.0-B-1 based on Z-scan, CCSDS 121.0-B-1, CCSDS 122.0-B-1 and JPEG-LS. And this algorithm is of less complexity, which is suitable for spaceborne system.