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In this study, a dual-tree complex wavelet transform (DTCWT) and convolutional sparse representation (CSR)-based image fusion method was proposed. In the proposed method, the infrared images and visible images were first decomposed by dual-tree complex wavelet transform to characterize their high-frequency bands and low-frequency band. Subsequently, the high-frequency bands were enhanced by guided filtering (GF), while the low-frequency band was merged through convolutional sparse representation and choose-max strategy. Lastly, the fused images were reconstructed by inverse DTCWT. In the experiment, the objective and subjective comparisons with other typical methods proved the advantage of the proposed method. To be specific, the results achieved using the proposed method were more consistent with the human vision system and contained more texture detail information.<\/jats:p>","DOI":"10.3233\/jifs-200554","type":"journal-article","created":{"date-parts":[[2020,6,26]],"date-time":"2020-06-26T18:43:31Z","timestamp":1593197011000},"page":"4617-4629","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":7,"title":["Infrared and visible image fusion using dual-tree complex wavelet transform and convolutional sparse representation"],"prefix":"10.1177","volume":"39","author":[{"given":"Chengrui","family":"Gao","sequence":"first","affiliation":[{"name":"Sichuan University, The College of Electronics Information and Engineering, Chengdu, China"}]},{"given":"Feiqiang","family":"Liu","sequence":"additional","affiliation":[{"name":"Sichuan University, The College of Electronics Information and Engineering, Chengdu, China"}]},{"given":"Hua","family":"Yan","sequence":"additional","affiliation":[{"name":"Sichuan University, The College of Electronics Information and Engineering, Chengdu, China"}]}],"member":"179","published-online":{"date-parts":[[2020,6,25]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2018.2887342"},{"key":"e_1_3_2_3_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2016.05.004"},{"key":"e_1_3_2_4_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2016.02.001"},{"key":"e_1_3_2_5_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2017.09.010"},{"key":"e_1_3_2_6_2","unstructured":"StathakiT. 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