Nature inspired optimization techniques for image processing—A short review
Authors: Anagnostopoulos, Theodoros 
Raju, K. Lova 
Ramson, S.R. Jino 
Vishnu, S. 
Issue Date: 1-Jan-2019
Book: Nature inspired optimization techniques for image processing applications 
Series: Intelligent Systems Reference Library
Keywords: Evolutionary algorithms, Image processing, Optimization techniques, Short review, Swarm intelligence algorithms
Abstract: 
Nature–inspired optimization techniques play an essential role in the field of image processing. It reduces the noise and blurring of images and also improves the image enhancement, image restoration, image segmentation, image edge detections, image generation, image fusion, image pattern recognition, image thresholding and so on. Several optimization techniques have been proposed so far for various applications of image processing. This chapter presents the short review of nature inspired optimization algorithms such as Genetic algorithm, Genetic programming, evolutionary strategies, Grey wolf optimization, Bat optimization, Ant colony optimization, Artificial Bee Colony optimization, Particle swarm optimization, Firefly optimization, Cuckoo Search Algorithm, Elephant Herding optimization, Bumble bees mating, Lion optimization, Water wave optimization, Chemical reaction optimization, Plant optimization, The raven roosting algorithm with the insight of applying optimization algorithms in advanced image processing fields.
ISBN: 978-3-319-96002-9
ISSN: 1868-4408
DOI: 10.1007/978-3-319-96002-9_5
URI: https://uniwacris.uniwa.gr/handle/3000/2663
Type: Book Chapter
Department: Department of Business Administration 
School: School of Administrative, Economics and Social Sciences 
Affiliation: University of West Attica (UNIWA) 
Appears in Collections:Book Chapter / Κεφάλαιο Βιβλίου

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