Color multi-focus image fusion algorithm based on fuzzy theory and dual-tree complex wavelet transform
Author(s) -
Yan Sun,
Ling Jiang
Publication year - 2017
Publication title -
journal of algorithms and computational technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.234
H-Index - 13
eISSN - 1748-3026
pISSN - 1748-3018
DOI - 10.1177/1748301816689686
Subject(s) - complex wavelet transform , artificial intelligence , mathematics , luminance , image fusion , color space , wavelet , algorithm , color image , wavelet transform , focus (optics) , computer vision , discrete wavelet transform , fuzzy logic , pattern recognition (psychology) , computer science , image processing , image (mathematics) , optics , physics
This paper puts forward a new color multi-focus image fusion algorithm based on fuzzy theory and dual-tree complex wavelet transform for the purpose of removing uncertainty when choosing sub-band coefficients in the smooth regions. Luminance component is the weighted average of the three color channels in the IHS color space and it is not sensitive to noise. According to the characteristics, luminance component was chosen as the measurement to calculate the focus degree. After separating the luminance component and spectrum component, Fisher classification and fuzzy theory were chosen as the fusion rules to conduct the choice of the coefficients after the dual-tree complex wavelet transform. So fusion color image could keep the natural color information as much as possible. This method could solve the problem of color distortion in the traditional algorithms. According to the simulation results, the proposed algorithm obtained better visual effects and objective quantitative indicators
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