一种适合于遥感图像的逐行扫描压缩算法

在ChristosChrysafis基于逐行小波变换编码的基础上,提出了一种低复杂性基于逐行扫描的图像压缩算法。该算法不需要对图像分块,在对小波系数进行均匀量化之后,根据不同子带的上下文统计特征进行概率建模,采用改进的低复杂性Golomb Rice算法进行熵编码。试验表明,采用这种算法,在对大幅面图像压缩时存储器需求远小于基于SPIHT等算法的存储器需求的同时,其熵编码复杂性也大幅降低,特别适合于功率和空间受限的遥感图像压缩系统中。

A Line-based Scan Compression Algorithm Suitable for Remote Sensing Images

In this paper, a line-based scan image compression algorithm with low complexity was presented. The algorithm was based on Christos Chrysafis's line-based wavelet transformation coding. There was not image tiling in the algorithm. The supposed algorithm modeled with contexts for different subband after quantifying wavelet coefficients uniformly. A modified Golomb-Rice algorithm with low complexity was adopted as entropy coder. The experiment shows that the memory requirement of the algorithm is far less than that of the SPIHT in compressing images with huge size. The complexity of the entropy coding of the algorithm is reduced largely. The algorithm is especially appropriate for remote sensing image compression system with power and space limited.