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• W2560669286 abstract "Abstract Digital images captured in outdoor environment are easily polluted by haze, which will degrade the conveyed information. To overcome this problem, a large number of researches have been conducted for image haze removal, among which the approach based on the dark channel prior assumption is in recent years considered as the state-of-the-art. This method is primarily dependent on consolidation of observations. However, in the proposed method, a theoretical perspective is adopted for image, which considers the degraded image as a product contaminated by noise. Two maps are constructed to label the noise severity and atmospheric light. The parameters involved are optimized via Particle Swarm Optimization with a penalty function in terms of hue change. Experimental results were compared with seven available approaches, along with an analysis on algorithm complexity. These analyses verify the effectiveness, efficiency, wide adaptability and theoretical soundness of the proposed approach." @default.
• W2560669286 created "2016-12-16" @default.
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• W2560669286 date "2017-08-01" @default.
• W2560669286 modified "2023-09-25" @default.
• W2560669286 title "Image de-hazing from the perspective of noise filtering" @default.
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• W2560669286 doi "https://doi.org/10.1016/j.compeleceng.2016.11.021" @default.
• W2560669286 hasPublicationYear "2017" @default.
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