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Dark and low-contrast image enhancement using dynamic stochastic resonance in discrete cosine transform domain
R.K. Jha, , K. Aizawa, P.K. Biswas
Published in Cambridge University Press
Volume: 2
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 systemcan be improved by addition of external noise. However, in the proposedDSR-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. © The Authors, 2013.
About the journal
JournalData powered by TypesetAPSIPA Transactions on Signal and Information Processing
PublisherData powered by TypesetCambridge University Press
Open AccessYes