Please use this identifier to cite or link to this item: https://idr.l1.nitk.ac.in/jspui/handle/123456789/15302
Full metadata record
DC FieldValueLanguage
dc.contributor.authorSuresh S.
dc.contributor.authorRagesh Rajan M.
dc.contributor.authorPushparaj J.
dc.contributor.authorCs A.
dc.contributor.authorLal S.
dc.contributor.authorReddy C.S.
dc.date.accessioned2021-05-05T10:26:52Z-
dc.date.available2021-05-05T10:26:52Z-
dc.date.issued2021
dc.identifier.citationInternational Journal of Remote Sensing , Vol. 42 , 13 , p. 5072 - 5090en_US
dc.identifier.urihttps://doi.org/10.1080/01431161.2021.1910367
dc.identifier.urihttp://idr.nitk.ac.in/jspui/handle/123456789/15302-
dc.description.abstractHaze 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 function. A final guided filter-based image refinement scheme is incorporated 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 performance 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. © 2021 Informa UK Limited, trading as Taylor & Francis Group.en_US
dc.titleDehazing of Satellite Images using Adaptive Black Widow Optimization-based frameworken_US
dc.typeArticleen_US
Appears in Collections:1. Journal Articles

Files in This Item:
There are no files associated with this item.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.