{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T04:18:19Z","timestamp":1784175499787,"version":"3.55.0"},"reference-count":37,"publisher":"MDPI AG","issue":"14","license":[{"start":{"date-parts":[[2022,7,20]],"date-time":"2022-07-20T00:00:00Z","timestamp":1658275200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Innovation and Practical Ability Cultivation Program for Postgraduates of Xi\u2019an Shiyou University","award":["YCS21211049"],"award-info":[{"award-number":["YCS21211049"]}]},{"name":"Innovation and Practical Ability Cultivation Program for Postgraduates of Xi\u2019an Shiyou University","award":["32015013"],"award-info":[{"award-number":["32015013"]}]},{"name":"Innovation and Practical Ability Cultivation Program for Postgraduates of Xi\u2019an Shiyou University","award":["2022GY-435"],"award-info":[{"award-number":["2022GY-435"]}]},{"name":"Science Fund of State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body","award":["YCS21211049"],"award-info":[{"award-number":["YCS21211049"]}]},{"name":"Science Fund of State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body","award":["32015013"],"award-info":[{"award-number":["32015013"]}]},{"name":"Science Fund of State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body","award":["2022GY-435"],"award-info":[{"award-number":["2022GY-435"]}]},{"name":"Shaanxi Province Key R&amp;D Program Project","award":["YCS21211049"],"award-info":[{"award-number":["YCS21211049"]}]},{"name":"Shaanxi Province Key R&amp;D Program Project","award":["32015013"],"award-info":[{"award-number":["32015013"]}]},{"name":"Shaanxi Province Key R&amp;D Program Project","award":["2022GY-435"],"award-info":[{"award-number":["2022GY-435"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>This paper presents an algorithm for infrared and visible image fusion using significance detection and Convolutional Neural Networks with the aim of integrating discriminatory features and improving the overall quality of visual perception. Firstly, a global contrast-based significance detection algorithm is applied to the infrared image, so that salient features can be extracted, highlighting high brightness values and suppressing low brightness values and image noise. Secondly, a special loss function is designed for infrared images to guide the extraction and reconstruction of features in the network, based on the principle of salience detection, while the more mainstream gradient loss is used as the loss function for visible images in the network. Afterwards, a modified residual network is applied to complete the extraction of features and image reconstruction. Extensive qualitative and quantitative experiments have shown that fused images are sharper and contain more information about the scene, and the fused results look more like high-quality visible images. The generalization experiments also demonstrate that the proposed model has the ability to generalize well, independent of the limitations of the sensor. Overall, the algorithm proposed in this paper performs better compared to other state-of-the-art methods.<\/jats:p>","DOI":"10.3390\/s22145430","type":"journal-article","created":{"date-parts":[[2022,7,21]],"date-time":"2022-07-21T03:34:40Z","timestamp":1658374480000},"page":"5430","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Infrared and Visible Image Fusion Method Using Salience Detection and Convolutional Neural Network"],"prefix":"10.3390","volume":"22","author":[{"given":"Zetian","family":"Wang","sequence":"first","affiliation":[{"name":"School of Electronic Engineering, Xi\u2019an Shiyou University, Xi\u2019an 710065, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fei","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Electronic Engineering, Xi\u2019an Shiyou University, Xi\u2019an 710065, China"},{"name":"State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, Hunan University, Changsha 410082, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dan","family":"Wu","sequence":"additional","affiliation":[{"name":"School of Electronic Engineering, Xi\u2019an Shiyou University, Xi\u2019an 710065, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guowang","family":"Gao","sequence":"additional","affiliation":[{"name":"School of Electronic Engineering, Xi\u2019an Shiyou University, Xi\u2019an 710065, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,7,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"153","DOI":"10.1016\/j.inffus.2018.02.004","article-title":"Infrared and visible image fusion methods and applications: A survey","volume":"45","author":"Ma","year":"2019","journal-title":"Inf. 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