Infrared and Visible Image Fusion Based on NSST and NSGA-III
To address the challenge of preserving structural information in image fusion techniques,a novel fusion method based on Non-Subsampled Shearlet Transform(NSST)and Non-dominated Sorting Genetic Algorithm Ⅲ(NSGA-Ⅲ)for infrared(IR)and visible(VIS)images is proposed.Firstly,the source images are decomposed into low-frequency and high-frequency sub-band images by using NSST.Secondly,image fusion is performed on these sub-images.Specifically,for the low-frequency images,a unique fusion rule based on NSGA-Ⅲ is introduced.It initially applies the regional energy fusion rule for pre-fusing the image.Using the pre-fusion image as a reference,an optimization process based on NSGA-Ⅲ algorithm is then carried out to obtain the final fused low-frequency image.Thirdly,the maxi-mum absolute value fusion rule is applied to merge high-frequency sub-bands.Finally,the fused image is reconstructed by using the inverse NSST.The performance of this proposed algorithm is rigorously validated on the TNO data set.Qualitative and quantitative results demonstrate that compared with other state-of-the-art fusion methods,the presented method can effectively enhance target visibility while simultaneously preserve the structural information.
infrared and visible image fusionpre-fusionNSGA-III algorithmNSST
NETL
NSTL
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