基于NSCT的多焦点图像融合算法

Yahao Yan, Junping Du, Qingping Li, Min Zuo, Jangmyung Lee
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引用次数: 4

摘要

针对同一场景下的多焦点图像融合问题,提出了一种基于非下采样Contourlet变换(NSCT)的多焦点图像融合算法。NSCT是二维分段光滑信号的稀疏表示,不仅满足各向异性尺度关系,具有多尺度、多向、平移不变性等特点,而且能够准确捕获图像的轮廓特征和纹理细节信息。该算法首先利用NSCT变换对源图像进行各个尺度和方向的分解,得到低通子带系数和带通方向子带系数。然后,在低通子带中采用加权盒计数维数融合规则,在带通方向子带中采用局部空间频率融合规则。最后,利用NSCT反变换得到融合图像。通过校验实验,证明了该算法简单有效。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multi-focus image fusion algorithm based on NSCT
This paper is aimed at the problem of Multi-focus image fusion for the same scene and has proposed a multi-focus image fusion algorithm based on NSCT [1] (The Nonsubsampled Contourlet Transform). NSCT is the sparse representation of a two-dimension piecewise smooth signals, not only satisfying the anisotropic scaling relation and having the multi-scale, multidirectional characteristics, and shift invariance, but also being able to accurately capture the image information of the contour feature and texture details. In proposed algorithm, NSCT transform is first used to decompose source images at each scale and direction to get low-pass sub-band coefficients and band-pass directional sub-band coefficients. Then, the fusion rule of weighted box-counting dimension is adopted in low-pass subband, as well as the fusion rule of local space frequency in band-pass directional sub-band. Finally, the NSCT inverse transform is employed to get the fused image. Through check experiment, our algorithm is proved to be simple and effective.
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