{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:25:02Z","timestamp":1760243102914,"version":"build-2065373602"},"reference-count":44,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2015,7,15]],"date-time":"2015-07-15T00:00:00Z","timestamp":1436918400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The crucial problem of infrared and visual image fusion is how to effectively extract the image features, including the image regions and details and combine these features into the final fusion result to produce a clear fused image. To obtain an effective fusion result with clear image details, an algorithm for infrared and visual image fusion through the fuzzy measure and alternating operators is proposed in this paper. Firstly, the alternating operators constructed using the opening and closing based toggle operator are analyzed. Secondly, two types of the constructed alternating operators are used to extract the multi-scale features of the original infrared and visual images for fusion. Thirdly, the extracted multi-scale features are combined through the fuzzy measure-based weight strategy to form the final fusion features. Finally, the final fusion features are incorporated with the original infrared and visual images using the contrast enlargement strategy. All the experimental results indicate that the proposed algorithm is effective for infrared and visual image fusion.<\/jats:p>","DOI":"10.3390\/s150717149","type":"journal-article","created":{"date-parts":[[2015,7,15]],"date-time":"2015-07-15T10:33:16Z","timestamp":1436956396000},"page":"17149-17167","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Infrared and Visual Image Fusion through Fuzzy Measure and Alternating Operators"],"prefix":"10.3390","volume":"15","author":[{"given":"Xiangzhi","family":"Bai","sequence":"first","affiliation":[{"name":"Image Processing Center, Beijing University of Aeronautics and Astronautics, Beijing 100191, China"},{"name":"State Key Laboratory of Virtual Reality Technology and Systems, Beihang University,  Beijing 100191, China\u00a0"}]}],"member":"1968","published-online":{"date-parts":[[2015,7,15]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2211","DOI":"10.1364\/OE.14.002211","article-title":"Multimodal near infrared spectral imaging as an exploratory tool for dysplastic esophageal lesion identification","volume":"14","author":"Lieber","year":"2006","journal-title":"Opt. 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