research-article

Wavelet-based contrast enhancement of dark images using dynamic stochastic resonance

Authors:

Rajlaxmi Chouhan,

Rajib Kumar Jha,

Prabir Kumar BiswasAuthors Info & Claims

ICVGIP '12: Proceedings of the Eighth Indian Conference on Computer Vision, Graphics and Image Processing

Article No.: 73, Pages 1 - 8

https://doi.org/10.1145/2425333.2425406

Published: 16 December 2012 Publication History

Abstract

In this paper, a dynamic stochastic resonance (DSR)-based technique has been proposed for contrast enhancement of dark and low contrast images in discrete wavelet transform (DWT) domain. Traditionally, the performance of a stochastic resonance (SR)-based system is improved by addition of external noise. However, in the proposed DSR-based approach, the internal noise of an image has been utilized for the purpose of contrast enhancement. The degradation due to inadequate illumination is treated as noise, and is used to produce a noise-induced transition of the image from a low-contrast state to a high-contrast state. Stochastic resonance is induced in the approximation and detail coefficients in an iterative fashion, producing an increase in variance and mean of the coefficient distribution. Optimal output response is ensured by selection of optimal of bistable system parameters. An iterative algorithm is followed to achieve target value of performance metrics, such as relative contrast enhancement factor (F), perceptual quality measures (PQM), and color enhancement factor (CEF), at minimum iteration count. When compared with the existing SR-based and non SR-based enhancement techniques in spatial and frequency domains, the proposed technique is found to give noteworthy performance in terms of contrast enhancement, perceptual quality, as well as colorfulness.

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Cited By

Kojima NLamsal BMatsumoto NYamashiro M(2019)Proposing autotuning image enhancement method using stochastic resonanceElectronics and Communications in Japan10.1002/ecj.12160102:4(35-46)Online publication date: 7-Mar-2019
https://dl.acm.org/doi/10.1002/ecj.12160
Kojima NLamsal BMatsumoto NYamashiro M(2018)Proposing Auto-tuning Image Enhancement Method using Stochastic Resonance確率共鳴を用いたオートチューニング画像強調法の提案IEEJ Transactions on Electronics, Information and Systems10.1541/ieejeiss.138.1425138:11(1425-1434)Online publication date: 1-Nov-2018
https://doi.org/10.1541/ieejeiss.138.1425
Ahmadi NAkbarizadeh G(2018)Iris tissue recognition based on GLDM feature extraction and hybrid MLPNN-ICA classifierNeural Computing and Applications10.1007/s00521-018-3754-0Online publication date: 4-Oct-2018
https://doi.org/10.1007/s00521-018-3754-0
Show More Cited By

Index Terms

Wavelet-based contrast enhancement of dark images using dynamic stochastic resonance
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision representations
        Image representations
      2. Computer vision tasks
  2. Computer graphics
    1. Image manipulation
2. Mathematics of computing
  1. Probability and statistics
    1. Stochastic processes

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cover image ACM Other conferences

ICVGIP '12: Proceedings of the Eighth Indian Conference on Computer Vision, Graphics and Image Processing

December 2012

633 pages

ISBN:9781450316606

DOI:10.1145/2425333

Program Chairs:
Bill Triggs
CNRS, France
,
Kavita Bala
Cornell University
,
Sharat Chandran
IIT Bombay, India

Copyright © 2012 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 16 December 2012

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ICVGIP '12

ICVGIP '12: The Eighth Indian Conference on Vision, Graphics and Image Processing

December 16 - 19, 2012

Mumbai, India

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Overall Acceptance Rate 95 of 286 submissions, 33%

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Cited By

Kojima NLamsal BMatsumoto NYamashiro M(2019)Proposing autotuning image enhancement method using stochastic resonanceElectronics and Communications in Japan10.1002/ecj.12160102:4(35-46)Online publication date: 7-Mar-2019
https://dl.acm.org/doi/10.1002/ecj.12160
Kojima NLamsal BMatsumoto NYamashiro M(2018)Proposing Auto-tuning Image Enhancement Method using Stochastic Resonance確率共鳴を用いたオートチューニング画像強調法の提案IEEJ Transactions on Electronics, Information and Systems10.1541/ieejeiss.138.1425138:11(1425-1434)Online publication date: 1-Nov-2018
https://doi.org/10.1541/ieejeiss.138.1425
Ahmadi NAkbarizadeh G(2018)Iris tissue recognition based on GLDM feature extraction and hybrid MLPNN-ICA classifierNeural Computing and Applications10.1007/s00521-018-3754-0Online publication date: 4-Oct-2018
https://doi.org/10.1007/s00521-018-3754-0
Chouhan RJha RBiswas P(2017)Hybrid Domain Analysis of Noise-Aided Contrast Enhancement Using Stochastic ResonanceJournal of Signal Processing Systems10.1007/s11265-016-1190-x89:2(243-262)Online publication date: 1-Nov-2017
https://dl.acm.org/doi/10.1007/s11265-016-1190-x
Bhardwaj NKaur GSingh P(2017)A Systematic Review on Image Enhancement TechniquesSensors and Image Processing10.1007/978-981-10-6614-6_23(227-235)Online publication date: 4-Oct-2017
https://doi.org/10.1007/978-981-10-6614-6_23
Gupta NKumar Jha R(2016)Enhancement of dark images using dynamic stochastic resonance with anisotropic diffusionJournal of Electronic Imaging10.1117/1.JEI.25.2.02301725:2(023017)Online publication date: 12-Apr-2016
https://doi.org/10.1117/1.JEI.25.2.023017
Chouhan RBiswas P(2015)Noise-aided dynamic range compression using selective processing in a statistics-dependent stochastic resonance model2015 Visual Communications and Image Processing (VCIP)10.1109/VCIP.2015.7457836(1-4)Online publication date: Dec-2015
https://doi.org/10.1109/VCIP.2015.7457836
Chouhan RBiswas PJha R(2015)Enhancement of low-contrast images by internal noise-induced Fourier coefficient rootingSignal, Image and Video Processing10.1007/s11760-015-0812-29:S1(255-263)Online publication date: 10-Sep-2015
https://doi.org/10.1007/s11760-015-0812-2
Chouhan RBiswas P(2014)Image enhancement and dynamic range compression using novel intensity-specific stochastic resonance-based parametric image enhancement model2014 IEEE International Conference on Image Processing (ICIP)10.1109/ICIP.2014.7025919(4532-4536)Online publication date: Oct-2014
https://doi.org/10.1109/ICIP.2014.7025919
Jha RChouhan R(2014)Dynamic stochastic resonance-based grayscale logo extraction in hybrid SVD-DCT domainJournal of the Franklin Institute10.1016/j.jfranklin.2014.01.017351:5(2938-2965)Online publication date: May-2014
https://doi.org/10.1016/j.jfranklin.2014.01.017
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