APSIPA Transactions on Signal and Information Processing > Vol 2 > Issue 1

Dark and low-contrast image enhancement using dynamic stochastic resonance in discrete cosine transform domain

Rajib Kumar Jha, Indian Institute of Technology Patna, India, jharajib@gmail.com , Rajlaxmi Chouhan, Indian Institute of Technology Kharagpur, India, Kiyoharu Aizawa, University of Tokyo, Japan, Prabir Kumar Biswas, Indian Institute of Technology Kharagpur, India
 
Suggested Citation
Rajib Kumar Jha, Rajlaxmi Chouhan, Kiyoharu Aizawa and Prabir Kumar Biswas (2013), "Dark and low-contrast image enhancement using dynamic stochastic resonance in discrete cosine transform domain", APSIPA Transactions on Signal and Information Processing: Vol. 2: No. 1, e6. http://dx.doi.org/10.1017/ATSIP.2013.7

Publication Date: 12 Nov 2013
© 2013 Rajib Kumar Jha, Rajlaxmi Chouhan, Kiyoharu Aizawa and Prabir Kumar Biswas
 
Subjects
 
Keywords
contrast enhancementdiscrete cosine transformdynamic stochastic resonanceperceptual quality measurecolored images
 

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In this article:
I. INTRODUCTION 
II. KEY CONTRIBUTION 
III. DYNAMIC STOCHASTIC RESONANCE 
IV. CHOICE OF DSR FOR IMAGE ENHANCEMENT 
V. MATHEMATICAL FORMULATION OF THE DCT-BASED DSR 
VI. SELECTION OF PARAMETERS FOR IMAGE ENHANCEMENT 
VII. PROPOSED DSR-BASED ALGORITHM FOR CONTRAST ENHANCEMENT 
VIII. EXPERIMENTAL RESULTS 
IX. GENERAL DISCUSSION 
X. CONCLUSIONS 

Abstract

A novel technique based on dynamic stochastic resonance (DSR) in discrete cosine transform (DCT) domain has been proposed in this paper for the enhancement of dark as well as low-contrast images. In conventional DSR-based techniques, the performance of a system can be improved by addition of external noise. However, in the proposed DSR-based work, the intrinsic noise of an image has been utilized to create a noise-induced transition of a dark image to a state of good contrast. The proposed technique significantly enhances the image contrast and color information without losing any image or color data by optimization of bistable system parameters. The performance of the proposed methodology has been measured in terms of relative contrast enhancement factor, perceptual quality measure, and color enhancement factor. When compared with the existing enhancement techniques, such as adaptive histogram equalization, gamma correction, single-scale retinex, multi-scale retinex, modified high-pass filtering, multicontrast enhancement with dynamic range compression, color enhancement by scaling, edge-preserving multi-scale decomposition, automatic control of imaging tool, and various spatial/frequency-domain SR-based techniques, the proposed technique gives remarkable performance in terms of contrast and color enhancement while ascertaining good perceptual quality.

DOI:10.1017/ATSIP.2013.7