基于RICE的遥感多光谱图像无损压缩算法

目前应用于遥感多光谱图像的无损压缩算法复杂度较高,不利于硬件实现.针对这一不足,这里根据遥感多光谱图像的成像特点,提出一种采用可逆的分量变换(RCT)对谱段信息重新分配,再利用优化的RICE算法对图像数据进行编码的无损压缩算法.实验表明,该算法所采用的分块计算k值、预测器预测和改进的熵编码器较原RICE熵编码器更适于硬件实现,且该算法复杂度低,执行效率高,更好地满足了星载图像无损压缩的要求.

Lossless Image Compression of Multispectral Remote Sensing Image based on Optimized RICE Algorithm

Nowadays most lossless compression algorithms used in multispectral sensing image processing are complex and not conducive to hardware implementation. A lossless image compression algorithm is proposed, thus to solve this problem by analyzing the characteristics of multispectral remote sensing image. This algorithm, with RCT （Reversible Component Transform）, rearranges the image data, then with optimized RICE algorithm, codes the data. Experiment results show that the K parameter by blocking calculation, predictor prediction and optimized RICE entropy encoder in algorithm are more suitable for hardware implementation. And this algorithm, with low complexity and high efficiency, could fairly meet the requirements of satellite lossless image compression.