基于自适应四叉树分割的遥感图像压缩算法

Compression of Remote Sensing Images Based on Adaptive Quadtree Partitioning

遥感图像具有不同于一般图像的特点 ,针对遥感图像对压缩算法的特殊要求 ,提出了自适应四叉树分割算法实现图像的分块 ,以各像块的均值近似表示该像块的灰度值 ,从而以尽量少的数据获得对原始图像的最佳逼近 ,再对逼近误差进行自适应分割和基于像块方差的自适应量化 ,最后对各分量进行Huffman编码。实验表明 ,本算法能表现出良好的实用性能 ,比JPEG算法更适用于遥感图像的压缩。

Remote sensing images have special properties compared with other images Considering the special requirements of the compression algorithm for remote sensing images, we proposed an adaptive quadtree partitioning algorithm to partition the image into blocks of different size The gray value of an image block is approximately represented by the mean of that block and the optimal approximation of the original image is then obtained with the amount of data as less as possible The approximation error image is adaptively divided and quantized based on the variance of each block Finally, each component is coded with Huffman code The experimental results show that our compression algorithm has excellent practical performance and is more suitable for the compression of remote sensing images than the JPEG algorithm