Please use this identifier to cite or link to this item:
Title: A Novel Adaptive Cuckoo Search Algorithm for Contrast Enhancement of Satellite Images
Authors: Suresh, S.
Lal, S.
Reddy, C.S.
Kiran, M.S.
Issue Date: 2017
Citation: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2017, Vol.10, 8, pp.3665-3676
Abstract: Owing to the increased demand for satellite images for various practical applications, the use of proper enhancement methods are inevitable. Visual enhancement of such images mainly focuses on improving the contrast of the scene procured, conserving its naturalness with minimum image artifacts. Last one decade traced an extensive use of metaheuristic approaches for automatic image enhancement processes. In this paper, a robust and novel adaptive Cuckoo search based Enhancement algorithm is proposed for the enhancement of various satellite images. The proposed algorithm includes a chaotic initialization phase, an adaptive Levy flight strategy and a mutative randomization phase. Performance evaluation is done by quantitative and qualitative results comparison of the proposed algorithm with other state-of-the-art metaheuristic algorithms. Box-and-whisker plots are also included for evaluating the stability and convergence capability of all the algorithms tested. Test results substantiate the efficiency and robustness of the proposed algorithm in enhancing a wide range of satellite images. 2008-2012 IEEE.
URI: 10.1109/JSTARS.2017.2699200
Appears in Collections:1. Journal Articles

Files in This Item:
File Description SizeFormat 
5 A Novel Adaptive Cuckoo.pdf1.1 MBAdobe PDFThumbnail

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