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The benchmarking for the selection of the best image dehazing intelligent algorithm based on multi-criteria perspectives is a challenging task owing to (a) multiple evaluation criteria, (b) criteria importance, (c) data variation, (d) criteria conflict, and (e) criteria tradeoff. A generally accepted framework for benchmarking image dehazing performance is unavailable in the existing literature. This study proposes a novel multi-perspective (i.e., an inhomogeneous foggy scene, a homogenous foggy scene, and a dark foggy scene) benchmarking framework for the selection of the best image dehazing intelligent algorithm based on multi-criteria analysis. Experiments were conducted in three stages. First was an evaluation experiment with five algorithms as part of matrix data. Second was a crossover between image dehazing intelligent algorithms and a set of target evaluation criteria to obtain matrix data. Third was the ranking of the image dehazing intelligent algorithms through integrated best\u2013worst and VIseKriterijumska Optimizacija I Kompromisno Resenje methods. Individual and group decision-making contexts were applied to demonstrate the efficiency of the proposed framework. The mean was used to objectively validate the ranks given by group decision-making contexts. Checklist and benchmarking scenarios were provided to compare the proposed framework with an existing benchmark study. The proposed framework achieved a significant result in terms of selecting the best image dehazing algorithm. <\/jats:p>","DOI":"10.1142\/s0219622020500169","type":"journal-article","created":{"date-parts":[[2020,6,11]],"date-time":"2020-06-11T14:56:52Z","timestamp":1591887412000},"page":"909-957","source":"Crossref","is-referenced-by-count":69,"title":["A Novel Multi-Perspective Benchmarking Framework for Selecting Image Dehazing Intelligent Algorithms Based on BWM and Group VIKOR Techniques"],"prefix":"10.1142","volume":"19","author":[{"given":"Karrar Hameed","family":"Abdulkareem","sequence":"first","affiliation":[{"name":"Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia"},{"name":"Faculty of Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia, 86400 Batu Pahat, Johor, Malaysia"}]},{"given":"Nureize","family":"Arbaiy","sequence":"additional","affiliation":[{"name":"Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia"}]},{"given":"A. 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