与一般图像不同,由于遥感影像具有纹理复杂、局部相关性较弱的特点,而且影像经过小波变换后系数的空间聚类特性较明显,因此遥感影像压缩具有一定的特殊性,可是目前大多数基于小波的压缩编码算法都没有考虑小波系数的空间聚类特性,为了进一步提高编码效率,提出了一种基于形态小波的遥感影像压缩算法。该算法首先对遥感影像进行多尺度快速小波变换,然后依据遥感影像的小波能量聚类特性,采用一种形态膨胀编码算法来实现遥感影像的高效压缩编码。试验结果表明,对一般遥感图像,该算法在高倍率压缩的情况下要优于目前的JPEG2000算法;而且对多波段的遥感影像,该算法也取得了较好的压缩效果。

This paper addresses the problem of image compression in remote sensing applications.Compared with other still images,remote-sensing images are characterized with complex textures and weak local correlation.By using wavelet transform,the coefficients have shown a spatial clustering trend in wavelet domain.Most of current algorithms of image compression have not taken this clustering trend into account.In order to further improve coding efficiency,an efficient remote sensing image coding algorithm based on morphological wavelet is proposed.First the fast multi-scale wavelet transform is applied to the image, then a morphological operator is designed to capture the clusters and fully exploit the redundancy between the coefficients.Compression is then achieved by using this non-linear method.For multi-bands remote-sensing images,a prior important band(PIB) method is firstly used to decorrelate the correlations in the spectral dimension,and the above coding algorithm is then applied to the bands.In the experiment,the authors select one AVARIS hyper-spectral image and two satellite images to test the performance of the algorithm.Experimental results illustrate that its performance is superior to JPEG2000 in low-bits compression and it is suitable to multi-band images too.