基于提升格式的高光谱遥感图像压缩算法

高光谱遥感的特点是谱分辨力的提高,但其高数据维给图像进一步处理带来了困难,因此有必要对其进行有效压缩处理.该文以提升格式为基础对高光谱图像压缩算法进行了研究,充分考虑了高光谱图像的空间相关性和谱间相关性,采用自适应波段选择的谱间压缩方法,通过自适应选择信息量大并且与其他波段相关性小的波段来降低高光谱数据量,然后采用梅花形网格分解方法构造出第二代小波变换,从而对二维图像进行空间压缩,可实现提升格式的分解和完全重构.实验结果表明,谱间压缩能够保留信息丰富的波段,同时计算复杂度大大降低,以提升格式为基础的第二代小波变换比第一代小波变换取得更好的空间压缩效果.

A compression algorithm of hyperspectral remote sensing image based on lifting scheme

Hyperspectral remote sensing images provide more spectral resolving power.However,an effective compression is needed to solve the problems brought about by high dimensions.To achieve this,a compression algorithm of a hyperspectral remote sensing image based on lifting scheme was developed.First,a dimensional reduction algorithm of adaptive band selection was proposed,which reduces dimensions by adaptively selecting high informative and low correlative bands.Second,the rectangular grids were split into quincunx grids to construct the second generation wavelets transformation and thereby realize spatial compression. Then the decomposition and absolute reconstruction were achieved.Experimental results show that spectrum compression can contain high informative bands and rapidly decrease computing complications,and second generation wavelets based on lifting scheme can achieve a better spatial compression effect than first generation wavelets.