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Bit-Plane Specific Selective Histogram Equalization for Image Enhancement and Representation

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Recent Trends in Image Processing and Pattern Recognition (RTIP2R 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1035))

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Abstract

Images acquired in poor acquisition conditions which are unavoidable and cannot be ignored in many visual applications require enhancement to achieve high contrast for better representation and interpretation of image objects. For efficient image storage and communications, compression and preserving of image details is required apart from contrast enhancement. A popular histogram equalization approach leaves undesirable artefacts in enhanced images and increases its data size due to excessive contrast enhancement. In this paper, we present a bit-plane specific selective histogram equalization technique which narrows the range of enhanced image than original image and keeps image details intact without unnoticeable artefacts with reduced image data size. The qualitative and quantitative measures as visual perception, histogram, edge details, entropy, data storage size, mean intensity and mean square error obtained for different images demonstrate the effectiveness of the selective bit-plane specific histogram equalization over to other methods of histogram equalization.

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Authors and Affiliations

  1. Hansraj College, University of Delhi, Delhi, India

    Arvind

  2. Scientific Analysis Group, Defence Research and Development Organization, Delhi, India

    Ram Ratan

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  1. Arvind
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  2. Ram Ratan
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Correspondence to Ram Ratan .

Editor information

Editors and Affiliations

  1. Department of Computer Science, University of South Dakota, Vermillion, SD, USA

    K. C. Santosh

  2. Solapur University, Solapur, India

    Ravindra S. Hegadi

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Arvind, Ratan, R. (2019). Bit-Plane Specific Selective Histogram Equalization for Image Enhancement and Representation. In: Santosh, K., Hegadi, R. (eds) Recent Trends in Image Processing and Pattern Recognition. RTIP2R 2018. Communications in Computer and Information Science, vol 1035. Springer, Singapore. https://doi.org/10.1007/978-981-13-9181-1_58

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  • DOI: https://doi.org/10.1007/978-981-13-9181-1_58

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  • Print ISBN: 978-981-13-9180-4

  • Online ISBN: 978-981-13-9181-1

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