Multi-focus image fusion using quality assessment of spatial domain and genetic algorithm

Jingbo Zhang, Xue Feng, Baoling Song, Mingjie Li, Yinghua Lu
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引用次数: 17

Abstract

For most image fusion algorithms split relationship among pixels and treat them more or less independently, this paper proposes a region based multi-focus image fusion scheme using quality assessment of spatial domain and genetic algorithm, which combines aspects of feature and pixel-level fusion. The basic idea is to divide the source images into blocks, and then select the corresponding blocks with higher quality assessment value to construct the resultant fused image. GA is brought forward to determine the suitable sizes of the block. Experimental results demonstrate that the proposed scheme outperforms Haar wavelet approach and morphological wavelet approach, both in visual effect and objective evaluation criteria, which is more robust under mis-registration situation.
基于空间域质量评价和遗传算法的多焦点图像融合
针对大多数图像融合算法将像素之间的关系分开,或多或少地独立处理的问题,本文提出了一种基于区域的多焦点图像融合方案,该方案采用空间域质量评估和遗传算法,将特征融合和像素级融合相结合。其基本思想是将源图像分割成若干块,然后选择质量评价值较高的相应块来构建融合后的图像。提出了遗传算法来确定合适的块尺寸。实验结果表明,该方法在视觉效果和客观评价标准上都优于Haar小波方法和形态小波方法,在误配情况下具有更强的鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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