迭代离散Shearlet变换异类源遥感图像融合

Shearlet变换是一种多尺度几何分析算法,适用于遥感这类纹理丰富、边缘复杂的图像处理。提出了一种基于迭代离散Shearlet变换的图像融合算法,将源图像进行分解,得到图像的多尺度、多方向树型结构表示;对粗糙分量和带通细节分量分别采用不同的融合规,得到融合图像的树型结构表示;最后进行Shearlet反变换得到融合图像。仿真结果表明,提出的算法比基于Contourlet变换的图像融合算法有更好的效果,更有利于保留纹理和边缘信息。

Remote sensing Image fusion based on iterative discrete Shearlet transform

Shearlet transform is one kind of multiscale geometric analysis tools.And it is useful at processing image with complex texture and edge.A remote sensing image fusion method based on iterative discrete Shearlet transform is proposed.This algorithm decomposes the source images into multiresolution and multidirection tree representations,and obtains the decomposed tree of the fusion image by different rules for the coarse and detail parts separately.At last,fusion image is got by invert discrete Shearlet transform.Experiments show this algorithm has better performance than image fusion methods based on Contourlet and keeps texture and edge more effectually.