A Compression Method for Remote Sensing Image
基于小波理论的遥感图像高保真压缩方法研究

With the increasing volumes of remote sensing data, data compression is receiving more and more attention. Adapting to the specialities of remote sensing data the low local correlation and the rich complex texture information, this paper presents an adaptive scalar vector hybrid quantization method for compression based on wavelet transform. According to textural intensity of every block in wavelet transformed high frequency subimage, we classify them into four classes. Compressing the plain block is at high compression ratio, and the textural block at high fidelity, The method enable the balance of the restore error of every block. This method is time efficient by avoiding the codebook training and searching, while surpass the performence of JPEG for single image. By combining with K L transformation, which is a kind of correlation reduction methods, we apply the presented method to multi band remote sensing image, and good results have been obtained.