Multi-focus image fusion method based on two-dimensional empirical mode decomposition (EMD) and genetic algorithm

Abstract

The invention relates to a multi-focus image fusion method based on two-dimensional empirical mode decomposition (EMD) and a genetic algorithm. At first, two-dimensional empirical mode decomposition (EMD) is performed on a source image, and therefore, the problem of weak correlation of local features of image fusion based on wavelet transform can be solved, and the problem of difficulty in wavelet basis function selection in a traditional wavelet method can be solved; high/low frequency selection is performed on obtained intrinsic mode function (IMF) components according to T-test, and then, fusion is performed on low-frequency components through adopting a regional information entropy maximum criterion, and regional correlation calculation is performed on high-frequency components, and components of which the correlations are in different threshold ranges are fused, and the selection of thresholds is searched through adopting the genetic algorithm, and therefore, the defects of experience determination of regional matching thresholds can be avoided; and finally, two-dimensional empirical mode decomposition (EMD) inverse transformation is performed on fused components so as to obtain fusion results. Thus, based on the combination of the two-dimensional empirical mode decomposition (EMD) and the genetic algorithm, and the multi-focus image fusion method can greatly improve the quality of fused images and has important significance and great use value in subsequent processing and image display of an application system.

Description

technical field [0001] The invention belongs to the field of multi-focus digital image fusion method and data information fusion, in particular to a multi-focus digital image fusion method based on two-dimensional EMD and genetic algorithm, which can be applied to various military or civilian multi-focus image fusion systems. Background technique [0002] Multi-focus image fusion means that multiple images formed due to different lens focus are processed to obtain a result image with clear target focus. [0003] At present, the commonly used multi-focus image fusion methods are mainly based on wavelet transform or higher level wavelet algorithm. Although the wavelet-based image fusion algorithm can decompose the image very well and get a good fusion result, the wavelet basis function [1] It has always been a difficult problem. Moreover, the image fusion based on wavelet transform is to fuse the local features of each pixel or small area, which will lead to the loss of the ...

AI Technical Summary

Problems solved by technology

Although the wavelet-based image fusion algorithm can decompose the image very well and get a good fusion result, the wavelet basis function [1] has always been a difficult problem

Moreover, the image fusion based on wavelet transform is to fuse the local features of each pixel or small area, which will lead to the loss of the strong correlation of local features.

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