基于多分辨率奇异值分解的图像融合

提出一种新的基于多分辨率奇异值分解（ MSVD）图像融合算法。算法对源图像进行MSVD处理，使其分解为互不相关的平滑和细节分量，并对平滑分量进行多层次的分解与处理。类似于小波变换，多分辨率奇异值分解的基本思想是在平滑分量的每一层上用奇异值分解（ SVD）来取代滤波，最终利用融合规则对图像进行MSVD融合。利用5种评价算子来评价算法，得到的融合效果很好。与基于小波分解的算法相比，算法计算简单、实时性突出，对复杂、高像素图像处理更简单方便。

Image Fusion Based on Multi-resolution Singular Value Decomposition

A novel image fusion algorithm based on multi-resolution singular value decomposition has been presented and evaluated. The images are processed with the MSVD algorithms and decomposed into unrelated smooth and detail components,and the smooth compo-nents are processed by the multi-level decomposition. Similar to the wavelet transform,the basic idea of the multi-resolution singular val-ue decomposition is to replace the filter with the Singular Value Decomposition （ SVD） on each layer of the smooth components. Finally MSVD integration is used with the image fusion rules. Five evaluation metrics are presented to evaluate the algorithm,and the algorithm achieves great performance. Compared with the algorithm based on wavelet decomposition,the algorithm presented is computing simply and its highlight is real-time performance,especially for high-pixels and complex images processing,which is more simple and conven-ient.