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

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Sensors and Image Processing

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 651))

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.

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Authors and Affiliations

  1. Department of CSE, ASET, Amity University Uttar Pradesh, Noida, India

    Gagandeep Kaur, Nishant Bhardwaj & Pradeep Kumar Singh

Authors
  1. Gagandeep Kaur
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  2. Nishant Bhardwaj
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  3. Pradeep Kumar Singh
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Correspondence to Gagandeep Kaur .

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Editors and Affiliations

  1. Gautam Buddha University, Greater Noida, Uttar Pradesh, India

    Shabana Urooj

  2. Department of Electrical and Instrumentation Engineering, Thapar University, Patiala, Punjab, India

    Jitendra Virmani

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Kaur, G., Bhardwaj, N., Singh, P.K. (2018). An Analytic Review on Image Enhancement Techniques Based on Soft Computing Approach. In: Urooj, S., Virmani, J. (eds) Sensors and Image Processing. Advances in Intelligent Systems and Computing, vol 651. Springer, Singapore. https://doi.org/10.1007/978-981-10-6614-6_26

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  • DOI: https://doi.org/10.1007/978-981-10-6614-6_26

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  • Online ISBN: 978-981-10-6614-6

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