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Nature Inspired Optimization Techniques for Image Processing—A Short Review

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Nature Inspired Optimization Techniques for Image Processing Applications

Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 150))

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.

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Authors and Affiliations

  1. Department of Electronics and Communication Engineering, Vignan’s Foundation for Science, Technology and Research, Guntur, Andhra Pradesh, India

    S. R. Jino Ramson, K. Lova Raju & S. Vishnu

  2. Department of Infocommunication Technologies, ITMO University, Saint Petersburg, Russia

    Theodoros Anagnostopoulos

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  1. S. R. Jino Ramson
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  2. K. Lova Raju
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  3. S. Vishnu
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  4. Theodoros Anagnostopoulos
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Correspondence to S. R. Jino Ramson .

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Editors and Affiliations

  1. Department of Electronics and Communication Engineering, Karunya University , Coimbatore, Tamil Nadu, India

    Jude Hemanth

  2. Department of Automation and Applied Informatics, Aurel Vlaicu University of Arad , Arad, Romania

    Valentina Emilia Balas

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Jino Ramson, S.R., Lova Raju, K., Vishnu, S., Anagnostopoulos, T. (2019). Nature Inspired Optimization Techniques for Image Processing—A Short Review. In: Hemanth, J., Balas, V. (eds) Nature Inspired Optimization Techniques for Image Processing Applications. Intelligent Systems Reference Library, vol 150. Springer, Cham. https://doi.org/10.1007/978-3-319-96002-9_5

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