Infrared Image Fusion Algorithm Selection Based on Joint Drop Shadow of Possibility Distributions

<p class="0abstract">To solve the fusion problem of visible and infrared images, based on image fusion algorithm such as region fusion, wavelet transform, spatial frequency, Laplasse Pyramid and principal component analysis, the quality evaluation index of image fusion was defined. Then, curve-let transform was used to replace the wavelet change to express the superiority of the curve. It integrated the intensity channel and the infrared image, and then transformed it to the original space to get the fused color image. Finally, two groups of images at different time intervals were used to carry out experiments, and the images obtained after fusion were compared with the images obtained by the first five algorithms, and the quality was evaluated. The experiment showed that the image fusion algorithm based on curve-let transform had good performance, and it can well integrate the information of visible and infrared images. It is concluded that the image fusion algorithm based on curve-let change is a feasible multi-sensor image fusion algorithm based on multi-resolution analysis. </p>

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Image Fusion Algorithm Selection Based on Fusion Validity Distribution Combination of Difference Features

Electronics ◽

10.3390/electronics10151752 ◽

2021 ◽

Vol 10 (15) ◽

pp. 1752

Author(s):

Linna Ji ◽

Fengbao Yang ◽

Xiaoming Guo

Keyword(s):

Image Fusion ◽

Combination Method ◽

Infrared Images ◽

Dual Mode ◽

Fusion Algorithm ◽

Algorithm Selection ◽

Fuzzy Operator ◽

Features Fusion ◽

Feature Score ◽

Selection Of

Aiming at addressing the problem whereby existing image fusion models cannot reflect the demand of diverse attributes (e.g., type or amplitude) of difference features on algorithms, leading to poor or invalid fusion effect, this paper puts forward the construction and combination of difference features fusion validity distribution based on intuition-possible sets to deal with the selection of algorithms with better fusion effect in dual mode infrared images. Firstly, the distances of the amplitudes of difference features between fused images and source images are calculated. The distances can be divided into three levels according to the fusion result of each algorithm, which are regarded as intuition-possible sets of fusion validity of difference features, and a novel construction method of fusion validity distribution based on intuition-possible sets is proposed. Secondly, in view of multiple amplitude intervals of each difference feature, this paper proposes a distribution combination method based on intuition-possible set ordering. Difference feature score results are aggregated by a fuzzy operator. Joint drop shadows of difference feature score results are obtained. Finally, the experimental results indicate that our proposed method can achieve optimal selection of algorithms that has relatively better effect on the fusion of difference features according to the varied feature amplitudes.

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