Abstract
An effective multi-focus image fusion algorithm based on random walk is proposed in this paper. Random walk and guided filter have attracted extensive attention in image fusion. Random walk is usually used to solve probability problems and it has a good smoothing effect, and guided filter can preserve the gradient information of the image well. The combination of two algorithms can better retain the edge information of the input image. Six sets of source images and five existing methods are used in the experiment and the experimental results show that the proposed algorithm outperforms the existing methods in both subjective and objective evaluation.
Highlights
Multi-focus images are a set of images obtained by the imaging equipment with different focal distances of the same scene
In order to solve the above problem, a multi-focus image fusion algorithm based on random walk and guided filter in spatial domain is proposed
A robust multi-focus image fusion method based on lazy random walks is proposed, which can obtain the fused images with few artifacts [25]
Summary
Multi-focus images are a set of images obtained by the imaging equipment with different focal distances of the same scene. In order to solve the above problem, a multi-focus image fusion algorithm based on random walk and guided filter in spatial domain is proposed. A robust multi-focus image fusion method based on lazy random walks is proposed, which can obtain the fused images with few artifacts [25]. A multi-focus image fusion algorithm based on guided filter and improved PCNN is proposed [29]. The guided filter cannot retain all the important features of the source image in the process of image fusion To solve this problem, a method combining static and dynamic filters [30] is proposed. Based on the above advantages, we combine random walk and guided filter to propose a multi-focus image fusion algorithm.
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