{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,19]],"date-time":"2026-04-19T19:23:32Z","timestamp":1776626612318,"version":"3.51.2"},"reference-count":49,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2020,12,29]],"date-time":"2020-12-29T00:00:00Z","timestamp":1609200000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the China Postdoctoral Science Foundation","award":["2013M540735"],"award-info":[{"award-number":["2013M540735"]}]},{"name":"the 111 Project","award":["B08038"],"award-info":[{"award-number":["B08038"]}]},{"name":"National Nature Science Foundation of China","award":["61701360, 61801359"],"award-info":[{"award-number":["61701360, 61801359"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The dark channel prior (DCP)-based single image removal algorithm achieved excellent performance. However, due to the high complexity of the algorithm, it is difficult to satisfy the demands of real-time processing. In this article, we present a Graphics Processing Unit (GPU) accelerated parallel computing method for the real-time processing of high-definition video haze removal. First, based on the memory access pattern, we propose a simple but effective filter method called transposed filter combined with the fast local minimum filter algorithm and integral image algorithm. The proposed method successfully accelerates the parallel minimum filter algorithm and the parallel mean filter algorithm. Meanwhile, we adopt the inter-frame atmospheric light constraint to suppress the flicker noise in the video haze removal and simplify the estimation of atmospheric light. Experimental results show that our implementation can process the 1080p video sequence with 167 frames per second. Compared with single thread Central Processing Units (CPU) implementation, the speedup is up to 226\u00d7 with asynchronous stream processing and qualified for the real-time high definition video haze removal.<\/jats:p>","DOI":"10.3390\/rs13010085","type":"journal-article","created":{"date-parts":[[2020,12,29]],"date-time":"2020-12-29T10:04:46Z","timestamp":1609236286000},"page":"85","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Accelerating Haze Removal Algorithm Using CUDA"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4450-3801","authenticated-orcid":false,"given":"Xianyun","family":"Wu","sequence":"first","affiliation":[{"name":"State Key Laboratory of Integrated Service Networks, Xidian University, Xi\u2019an 710071, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9545-718X","authenticated-orcid":false,"given":"Keyan","family":"Wang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Integrated Service Networks, Xidian University, Xi\u2019an 710071, China"}]},{"given":"Yunsong","family":"Li","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Integrated Service Networks, Xidian University, Xi\u2019an 710071, China"}]},{"given":"Kai","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Xidian University, Xi\u2019an 710071, China"}]},{"given":"Bormin","family":"Huang","sequence":"additional","affiliation":[{"name":"School of Information Science and Technology, Southwest Jiaotong University, Chengdu 611756, China"}]}],"member":"1968","published-online":{"date-parts":[[2020,12,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Tan, R. 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