An Analytic Review on Image Enhancement Techniques Based on Soft Computing Approach

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DC Field	Value	Language
dc.contributor.author	Kaur, Gagandeep	-
dc.contributor.author	Bhardwaj, Nishant	-
dc.contributor.author	Singh, Pradeep Kumar	-
dc.date.accessioned	2022-07-14T09:15:12Z	-
dc.date.available	2022-07-14T09:15:12Z	-
dc.date.issued	2018	-
dc.identifier.uri	http://ir.juit.ac.in:8080/jspui//xmlui/handle/123456789/4195	-
dc.description	© Springer Nature Singapore Pte Ltd. 2018 S. Urooj and J. Virmani (eds.), Sensors and Image Processing, Advances in Intelligent Systems and Computing 651, https://doi.org/10.1007/978-981-10-6614-6_26	en_US
dc.description.abstract	This paper discusses various image enhancement techniques using soft computing approaches. The approaches used are genetic algorithm, fuzzy-based enhancement, neural networks, and optimization techniques (ant colony, bee colony, particle swarm optimization, etc.). The main objective of this paper is to identify the status of currently used soft computing approaches in image enhancement. Our study may help future researchers to overcome the current issues with existing approaches to improve the overall image quality.	en_US
dc.language.iso	en	en_US
dc.publisher	Jaypee University of Information Technology, Solan, H.P.	en_US
dc.subject	Image enhancement	en_US
dc.subject	Image quality	en_US
dc.subject	Digital image processing	en_US
dc.subject	Soft computing	en_US
dc.title	An Analytic Review on Image Enhancement Techniques Based on Soft Computing Approach	en_US
dc.type	Book chapter	en_US
Appears in Collections:	Book Chapters

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