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Histogram Equalization Variants as Optimization Problems: A Review

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Abstract

In the consumer electronics field, the main challenge in image processing is to preserve the original brightness. Histogram Equalization (HE) is one of the simplest and widely used methods for contrast enhancement. However, HE does not suit into the consumer electronics field as this procedure flattens the histogram by distributing the entire gray levels uniformly. Therefore, several HE variants have been proposed based on proper histogram segmentation, histogram weighting, and range optimization techniques to overcome this flattening effect. However, sometimes these modifications become complex and computationally expensive. Recently, researchers have formulated the HE variants for image enhancement as optimization problems and solved, using Nature-Inspired Optimization Algorithms (NIOA), which starts a new era in the image enhancement field. This study presents an up-to-date review over the application of NIOAs for HE variants in image enhancement domain. The main issues which are involved in the application of NIOAs with HE are also discussed here.

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  1. Department of Computer Science and Application, Midnapore College (Autonomous), Paschim Medinipur, West Bengal, India

    Krishna Gopal Dhal

  2. Department of Information Technology, Kalyani Government Engineering College, Kalyani, Nadia, India

    Arunita Das

  3. Learningmate Solutions Pvt. Ltd., Kolkata, West Bengal, India

    Swarnajit Ray

  4. Departamento de Electrónica, Universidad de Guadalajara, CUCEI Av. Revolución 1500, 44430, Guadalajara, Mexico

    Jorge Gálvez

  5. Department of Engineering and Technological Studies, University of Kalyani, Kalyani, Nadia, India

    Sanjoy Das

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Dhal, K.G., Das, A., Ray, S. et al. Histogram Equalization Variants as Optimization Problems: A Review. Arch Computat Methods Eng 28, 1471–1496 (2021). https://doi.org/10.1007/s11831-020-09425-1

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