基于不同小波变换与同态滤波结合的CBERS-02B卫星CCD图像的薄云去除

Removing Thin Cloud by Combining Wavelet Transforms and Homomorphic Filter in the CBERS-02B Image

卫星CCD图像的去云处理对遥感信息的增强与提取有重要的意义,尤其是在云覆盖严重的低纬度地区。为去除CBERS-02B卫星CCD图像中薄云的影响,分别使用Mallat和à trous 2种小波变换对图像进行分解;利用同态滤波对2种小波分解图像的低频系数进行处理,衰减其低频信息;将处理后的小波低频系数与分解的高频系数进行小波重构,从而达到去云的目的。定量分析基于Mallat和à trous小波变换结合同态滤波法的去云结果表明,经à trous小波变换结合同态滤波法的去云影像所包含信息量大,细节信息丰富,去云效果较好。

It is important to remove cloud in the CCD images of satellite for enhancing and extracting remote sensing information,especially in low latitude areas.In order to remove thin cloud in the CBERS-02B CCD images,two different forms of wavelet transforms were used.Low-frequency coefficients that are decomposed by two wavelet transforms are processed by homomorphic filter separately for lowing its low-frequency information.Results is reconstructed with low-frequency coefficients and high-frequency coefficients which decomposed from Mallat and  trous wavelet transform.According to quantitative evaluation, trous wavelet transform combining with homomorphic filter algorithm can produce good results in thin cloud removal with higher entropy and standard deviation.It also can retain a large amount of information and rich detail information.