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Infrared and visible image Fusion Based on Res2Net-Transformer Automatic Encoding and Decoding

Computers, Materials & Continua 2024年第4期79卷 1441-1461页

作者： Chunming Wu Wukai Liu Xin Ma Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology School of Electrical EngineeringNortheast Electric Power UniversityJilin132012China School of Electrical Engineering Northeast Electric Power UniversityJilin132012China School of Aeronautical Engineering Jilin Institute of Chemical TechnologyJilin132022China

A novel image fusion network framework with an autonomous encoder and decoder is suggested to increase thevisual impression of fused images by improving the quality of infrared and visible light picture fusion. The networkcomprises an encoder module, fusion layer, decoder module, and edge improvementmodule. The encoder moduleutilizes an enhanced Inception module for shallow feature extraction, then combines Res2Net and Transformerto achieve deep-level co-extraction of local and global features from the original picture. An edge enhancementmodule (EEM) is created to extract significant edge features. A modal maximum difference fusion strategy isintroduced to enhance the adaptive representation of information in various regions of the source image, therebyenhancing the contrast of the fused image. The encoder and the EEM module extract features, which are thencombined in the fusion layer to create a fused picture using the decoder. Three datasets were chosen to test thealgorithmproposed in this paper. The results of the experiments demonstrate that the network effectively preservesbackground and detail information in both infrared and visible images, yielding superior outcomes in subjectiveand objective evaluations.

关键词： image fusion Res2Net-Transformer infrared image visible image

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Sub-Regional Infrared-visible image Fusion Using Multi-Scale Transformation

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Journal of Beijing Institute of Technology 2022年第6期31卷 535-550页

作者： Yexin Liu Ben Xu Mengmeng Zhang Wei Li Ran Tao School of Information and Electronics Beijing Institute of Technology

Infrared-visible image fusion plays an important role in multi-source data fusion, which has the advantage of integrating useful information from multi-source sensors. However, there are still challenges in target enhancement and visual improvement. To deal with these problems, a subregional infrared-visible image fusion method(SRF) is proposed. First, morphology and threshold segmentation is applied to extract targets interested in infrared images. Second, the infrared background is reconstructed based on extracted targets and the visible image. Finally, target and background regions are fused using a multi-scale transform. Experimental results are obtained using public data for comparison and evaluation, which demonstrate that the proposed SRF has potential benefits over other methods.

关键词： image fusion infrared image multi-scale transform visible image

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image Fusion Based on Bioinspired Rattlesnake Visual Mechanism Under Lighting Environments of Day and Night Two Levels

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Journal of Bionic Engineering 2024年第3期21卷 1496-1510页

作者： Yong Wang Hongmin Zou College of Communication Engineering Jilin UniversityChangchun130012China

This study,grounded in Waxman fusion method,introduces an algorithm for the fusion of visible and infrared images,tailored to a two-level lighting environment,inspired by the mathematical model of the visual receptive field of rattlesnakes and the two-mode cells'*** research presented here is segmented into three *** the first segment,we design a preprocessing module to judge the ambient light intensity and divide the lighting environment into two levels:day and *** second segment proposes two distinct network structures designed specifically for these daytime and nighttime *** the daytime images,where visible light information is predominant,we feed the ON-VIS signal and the IR-enhanced visual signal into the central excitation and surrounding suppression regions of the ON-center receptive field in the B channel,***,for nighttime images where infrared information takes precedence,the ON-IR signal and the Visual-enhanced IR signal are separately input into the central excitation and surrounding suppression regions of the ON-center receptive field in the B *** outcome is a pseudo-color fused *** third segment employs five different no-reference image quality assessment methods to evaluate the quality of thirteen sets of pseudo-color images produced by fusing infrared and visible *** images are then compared with those obtained by six other methods cited in the relevant *** empirical results indicate that this study's outcomes surpass the comparative results in terms of average gradient and spatial *** one or two sets of fused images underperformed in terms of standard deviation and entropy when compared to the control *** sets of fused images did not perform as well as the comparison in the QAB/F *** conclusion,the fused images generated through the proposed method show superior performance in terms of scene detail,visual perception,and image sharpness

关键词： Rattlesnake visible image Infrared image Daylight Bionic

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Pseudo Color Fusion of Infrared and visible images Based on the Rattlesnake Vision Imaging System

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Journal of Bionic Engineering 2022年第1期19卷 209-223页

作者： Yong Wang Hongqi Liu Xiaoguang Wang College of Communication Engineering Jilin UniversityChangchun130012China Public Computer Education and Research Center Jilin UniversityChangchun130012China

image fusion is a key technology in the field of digital image *** the present study,an effect-based pseudo color fusion model of infrared and visible images based on the rattlesnake vision imaging system(the rattlesnake bimodal cell fusion mechanism and the visual receptive field model)is *** innovation point of the proposed model lies in the following three features:first,the introduction of a simple mathematical model of the visual receptive field reduce computational complexity;second,the enhanced image is obtained by extracting the common information and unique information of source images,which improves fusion image quality;and third,the Waxman typical fusion structure is improved for the pseudo color image fusion *** performance of the image fusion model is verified through comparative *** the subjective visual evaluation,we find that the color of the fusion image obtained through the proposed model is natural and can highlight the target and scene *** the objective quantitative evaluation,we observe that the best values on the four indicators,namely standard deviation,average gradient,entropy,and spatial frequency,accounts for 90%,100%,90%,and 100%,respectively,indicating that the fusion image exhibits superior contrast,image clarity,information content,and overall *** results reveal that the performance of the proposed model is superior to that of other models and thus verified the validity and reliability of the model.

关键词： Bionic Rattlesnake Bimodal cell Infrared image visible image image fusion

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