基于小波变换的SAR图像自适应子带编码算法

An Algorithm of Adaptive Subband Coding for SAR Image Based on Wavelet Transform

为降低大数据量SAR图像对传输带宽和存储空间的要求,必须对SAR图像进行高效压缩。基于小波变换的传统SAR图像压缩方法只对低频子带进行分解处理,造成SAR图像处于中高频子带的重要纹理信息丢失。针对上述问题,提出一种基于小波变换的自适应SAR图像压缩算法。首先对图像进行小波软阈值消噪预处理,然后依据能量指标,进行子带重要性判定,对认定为重要的子带进行深一层次分解,分解完成后对所有子带进行恒定比特率条件下的最小误差量化,实现对图像的自适应压缩。仿真实验表明:该算法能很好地保护SAR图像的高频细节,提高了信噪比。

In order to store and transmit largely and efficiently,SAR images must be compressed effectually.The traditional coding method of SAR image based on wavelet translation can only be used to decompose low frequency,so a lot of information of intermediate/high frequency is lost.In view of the above problem,this paper presents an adaptive SAR image compression algorithm based on wavelet transform.In this paper,the speckle noise is reduced to improve the image quality first.And then according to the energy index,the SAR image is decomposed into a series of subbands,which have different significances.Finally,all the subbands are quantized by the minimal error quantization at the same bit rate.The use of the algorithm can protect the high frequency details of SAR image adequately,and can achieve a better compression result.