基于多分辨奇异值分解的多聚焦图像融合

Multi-focus image fusion based on multi-resolution singular value decomposition

提出了一种多分辨奇异值分解(MSVD)的新框架,并把它应用于多聚焦图像融合中。基于分块算法原理,利用奇异值分解获得具有不同分辨率的一幅近似和三幅细节图像。结合重构算法,给出了图像的融合框架。对比基于离散小波变换(DWT)的融合算法,基于MSVD的融合效果更好,而且MSVD的基向量只依赖于图像本身而不像小波需要固定的基。采用客观性能指标对结果图像进行评价。实验结果表明,提出的方法不仅简单易行,而且图像表现出良好的视觉效果,清晰度和空间频率都有很大提高。

A new frame of multi-resolution singular value decomposition（MSVD） was presented and applied into multi-focus image fusion.Based on the principle of blocking algorithm,images involved in fusion were decomposed into one approximation and three detail images with different resolution by singular value decomposition.Combined with reconstruction algorithm of MSVD,the frame of image fusion was given.Compared with image fusion by discrete wavelet transform（DWT）,image fusion by MSVD performs better.Moreover,MSVD does not have a fixed set of basis like wavelet,and its basis vectors depend on the image itself.The performance of the result image was evaluated using objective indices.The experimental result shows that not only the proposed method is simple,but also that the visual effect of the image is considerable after reducing blocking artifact.And both the definition and spatial frequency are improved greatly.