Multi-focus image fusion based on the neighbor distance

Authors:
Hengjun Zhao;Zhaowei Shang;Yuan Yan Tang;Bin Fang
Affiliations:
College of Computer Science, Chongqing University, Chongqing 400030, China;College of Computer Science, Chongqing University, Chongqing 400030, China;College of Computer Science, Chongqing University, Chongqing 400030, China and Faculty of Science and Technology, University of Macau, Macau, China;College of Computer Science, Chongqing University, Chongqing 400030, China
Venue:
Pattern Recognition
Year:
2013

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Abstract

The effective measurement of pixel's sharpness is a key factor in multi-focus image fusion. In this paper, a gray image is considered as a two-dimensional surface, and the neighbor distance deduced from the oriented distance in differential geometry is used as a measure of pixel's sharpness, where the smooth image surface is restored by kernel regression. Based on the deduced neighbor distance filter, we construct a multi-scale image analysis framework, and propose a multi-focus image fusion method based on the neighbor distance. The experiments demonstrate that the proposed method is superior to the conventional image fusion methods in terms of some objective evaluation indexes, such as spatial frequency, standard deviation, average gradient, etc.