{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,19]],"date-time":"2026-03-19T23:40:09Z","timestamp":1773963609216,"version":"3.50.1"},"reference-count":45,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2024,7,11]],"date-time":"2024-07-11T00:00:00Z","timestamp":1720656000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Shaanxi Province\u2019s key research and development plan","award":["2024GX-YBXM-526"],"award-info":[{"award-number":["2024GX-YBXM-526"]}]},{"name":"Shaanxi Province\u2019s key research and development plan","award":["2023-YBGY-025"],"award-info":[{"award-number":["2023-YBGY-025"]}]},{"name":"Shaanxi Province\u2019s key research and development plan","award":["24GXFW0045"],"award-info":[{"award-number":["24GXFW0045"]}]},{"name":"Xi\u2019an Science and Technology Plan Project University Institute Science and Technology Personnel Service Enterprise Project","award":["2024GX-YBXM-526"],"award-info":[{"award-number":["2024GX-YBXM-526"]}]},{"name":"Xi\u2019an Science and Technology Plan Project University Institute Science and Technology Personnel Service Enterprise Project","award":["2023-YBGY-025"],"award-info":[{"award-number":["2023-YBGY-025"]}]},{"name":"Xi\u2019an Science and Technology Plan Project University Institute Science and Technology Personnel Service Enterprise Project","award":["24GXFW0045"],"award-info":[{"award-number":["24GXFW0045"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Imaging"],"abstract":"<jats:p>Haze weather deteriorates image quality, causing images to become blurry with reduced contrast. This makes object edges and features unclear, leading to lower detection accuracy and reliability. To enhance haze removal effectiveness, we propose an image dehazing and fusion network based on the encoder\u2013decoder paradigm (UIDF-Net). This network leverages the Image Fusion Module (MDL-IFM) to fuse the features of dehazed images, producing clearer results. Additionally, to better extract haze information, we introduce a haze encoder (Mist-Encode) that effectively processes different frequency features of images, improving the model\u2019s performance in image dehazing tasks. Experimental results demonstrate that the proposed model achieves superior dehazing performance compared to existing algorithms on outdoor datasets.<\/jats:p>","DOI":"10.3390\/jimaging10070164","type":"journal-article","created":{"date-parts":[[2024,7,11]],"date-time":"2024-07-11T15:59:48Z","timestamp":1720713588000},"page":"164","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["UIDF-Net: Unsupervised Image Dehazing and Fusion Utilizing GAN and Encoder\u2013Decoder"],"prefix":"10.3390","volume":"10","author":[{"given":"Anxin","family":"Zhao","sequence":"first","affiliation":[{"name":"School of Communication and Information Engineering, Xi\u2019an University of Science and Technology, Xi\u2019an 710054, China"}]},{"given":"Liang","family":"Li","sequence":"additional","affiliation":[{"name":"School of Communication and Information Engineering, Xi\u2019an University of Science and Technology, Xi\u2019an 710054, China"}]},{"given":"Shuai","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Communication and Information Engineering, Xi\u2019an University of Science and Technology, Xi\u2019an 710054, China"}]}],"member":"1968","published-online":{"date-parts":[[2024,7,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Che, C., Zheng, H., Huang, Z., Jiang, W., and Liu, B. 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