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Modified Histogram Segmentation Bi-Histogram Equalization

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Advanced Computing and Intelligent Engineering

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1082))

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Abstract

In the application of image processing, contrast enhancement is a major step. Conventional methods which are studied in contrast enhancement such as Histogram Equalization (HE) have not satisfactory results on many different low-contrast images and they also cannot automatically handle different images. These problems result of specifying parameters manually in order to produce high contrast images. In this paper, Modified Histogram Segmentation Bi-Histogram Equalization (MHSBHE) is proposed. In this study, histogram is modified before segmentation to improve the input image contrast. The proposed method accomplishes multi goals of preserving brightness, retaining the shape features of the original histogram and controlling excessive enhancement rate, suiting for applications of consumer electronics. MHSBHE avoids over-enhancement and generates images with natural improvement. Simulation results show that in terms of visual assessment, peak signal-to-noise (PSNR), average information content (entropy) and Absolute Mean Brightness Error (AMBE) the proposed method has better results compared to literature methods. The proposed method enhances the natural appearance of images especially in no static range images and the improved image is helpful in generation of the consumer electronic.

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Author information

Authors and Affiliations

  1. Medical Informatics Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran

    Mitra Montazeri

  2. Computer Engineering Department, Shahid Bahonar University, Kerman, Iran

    Mitra Montazeri

Authors
  1. Mitra Montazeri
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Correspondence to Mitra Montazeri .

Editor information

Editors and Affiliations

  1. Department of Computer Science, Rama Devi Women’s University, Bhubaneswar, Odisha, India

    Bibudhendu Pati

  2. Department of Computer Science, Rama Devi Women’s University, Bhubaneswar, Odisha, India

    Chhabi Rani Panigrahi

  3. Cloud Computing, The University of Melbourne, Melbourne, VIC, Australia

    Rajkumar Buyya

  4. Department of Computer Science and Information Engineering, Providence University, Taichung, Taiwan

    Kuan-Ching Li

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Montazeri, M. (2020). Modified Histogram Segmentation Bi-Histogram Equalization. In: Pati, B., Panigrahi, C., Buyya, R., Li, KC. (eds) Advanced Computing and Intelligent Engineering. Advances in Intelligent Systems and Computing, vol 1082. Springer, Singapore. https://doi.org/10.1007/978-981-15-1081-6_38

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  • DOI: https://doi.org/10.1007/978-981-15-1081-6_38

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-1080-9

  • Online ISBN: 978-981-15-1081-6

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