Dehazing of Satellite Images using Adaptive Black Widow Optimization-based framework

Suresh, Shilpa and Rajan, Ragesh M and Pushparaj, Jagalingam and Asha, C S and Shyam, Lal and Reddy, Chintala Sudhakar (2021) Dehazing of Satellite Images using Adaptive Black Widow Optimization-based framework. Remote Sensing Applications: Society and Environment, 42 (13). pp. 5068-5086. ISSN 2352-9385

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Haze is a common atmospheric disturbance that adversely affects the quality of optical data, thus often restricting their usability. Since these effects are inherent in the process of spaceborne Earth sensing, it is important to develop effective methods to remove them. This work proposes a novel method for de-hazing satellite imagery and outdoor camera images. It is developed by modifying the transmission map used in Dark Channel Prior (DCP) method. A Weighted Variance Guided Filter (WVGF) is introduced for enhancing the image quality, which included a two-stage image decomposition and fusion process. The method also optimally combines the radiance and transmission components along with an additional stage modelling a fusion-based transparency func�tion. A final guided filter-based image refinement scheme is incor�porated to improve the processed image quality. The optimal tuning of the image-dependent parameters at various stages is achieved using the newly proposed Adaptive Black Widow Optimization (ABWO) algorithm, which makes the proposed de�hazing scheme fully automatic. Qualitative and quantitative perfor�mance analyses, and the results are compared with other state-of�the-art methods. The experimental results reveal that the proposed method performs better as compared with others, independent of the haze density, without losing the natural look of the scene.

Item Type: Article
Subjects: Engineering > MIT Manipal > Mechatronics
Depositing User: MIT Library
Date Deposited: 20 Jan 2022 09:05
Last Modified: 20 Jan 2022 09:05

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