Compression of Remote Sensing Images Based on Adaptive Quadtree Partitioning
基于自适应四叉树分割的遥感图像压缩算法

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