基于小波理论的矢量量化遥感图像压缩方法

Compression of remote-sensing images based on Wavelet transform and vector quantization

分析了遥感图像的统计特性,提出了适合遥感图像压缩的矢量量化与小波变换相结合的压缩方法。该方法将遥感图像小波变换后高频子图划分为一定大小的的像块,对局部相关性较强、灰度变化较小的像块进行高倍压缩;对局部相关性较小、灰度变化较大的像块进行高保真压缩。实验表明,本方法具有良好的压缩性能,适用于遥感图像的压缩。

This paper studies the compression of remote-sensing images based on Wavelet analysis and vector quantization(VQ). It is well known that tradition VQ has speed problem of codebook training and searching. In order to improve the time efficient, a non-codebook VQ method is provided. The energy of image will be re-(allocation) after Wavelet transform. There is more difference of textural intensity between blocks in Wavelet-transformed high-frequency subimages. Compressing the plain block is at high compression ratio, and the textural block at high fidelity. Comparison with tradition VQ, this method can obtain high compression ratio and good image quality, and avoids the codebook training in encoding and decoding process.