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Recent advancement in haze removal approaches

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Abstract

Haze and fog are big reasons for road accidents. The haze occurrence in the air lowers the images quality captured by visible camera sensors. Haze brings inconvenience to numerous computer vision applications as it diminishes the scene visibility. Haze removal techniques recuperate the color and scene contrast. These haze removal techniques are extensively utilized in numerous applications like outdoor surveillance, object detection, consumer electronics, etc. Haze removal is commonly performed under the physical degradation model, which requires a solution of an ill-posed inverse issue. Different dehazing algorithms was recently proposed to relieve this difficulty and has acknowledged a great deal of consideration. Dehazing is basically accomplished through four major steps: hazy images acquisition process, estimation process (atmospheric light, transmission map, scattering phenomenon, and visibility or haze level), enhancement process (improved visibility level, reduce haze or noise level), restoration process (restore enhanced image, image reconstruction). This four-step dehazing process makes it possible to provide a step-by-step approach to the complex solution of the ill-posed inverse problem. Our detailed survey and experimental analysis on different dehazing methods that will help readers understand the effectiveness of the individual step of the dehazing process and will facilitate development of advanced dehazing algorithms. The overall objective of this review paper is to explore the various methods for efficiently removing the haze and short comings of the earlier presented techniques used in the revolutionary era of image processing applications.

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Funding

This work was partly supported by the National Key Research and Development Project (2016YFC1000307-3), the National Natural Science Foundation of China (61806032 and 61976031), the Chongqing Research Program of Application Foundation & Advanced Technology (cstc2018jcyjAX0117) and the Scientific & Technological Key Research Program of Chongqing Municipal Education Commission (KJZD-K201800601)

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Authors and Affiliations

  1. Chongqing Key Laboratory of Image Cognition, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China

    Hira Khan, Bin Xiao & Weisheng Li

  2. Department of Information Technology and Computer Science, Pak-Austria Fachhochschule Institute of Applied Sciences and Technology, Haripur, Pakistan

    Nazeer Muhammad

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  1. Hira Khan
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  2. Bin Xiao
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  3. Weisheng Li
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  4. Nazeer Muhammad
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Correspondence to Bin Xiao.

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Communicated by B-K Bao.

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Khan, H., Xiao, B., Li, W. et al. Recent advancement in haze removal approaches. Multimedia Systems 28, 687–710 (2022). https://doi.org/10.1007/s00530-021-00865-8

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