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Proceedings ArticleDOI

Internal noise-induced contrast enhancement of dark images

TLDR
The proposed contrast enhancement technique using scaling of internal noise of a dark image in discrete cosine transform (DCT) domain adopts a local adaptive processing and significantly enhances the image contrast and color information while ascertaining good perceptual quality.
Abstract
A contrast enhancement technique using scaling of internal noise of a dark image in discrete cosine transform (DCT) domain has been proposed in this paper. The mechanism of enhancement is attributed to noise-induced transition of DCT coefficients from a poor state to an enhanced state. This transition is effected by the internal noise present due to lack of sufficient illumination and can be modeled by a general bistable system exhibiting dynamic stochastic resonance. The proposed technique adopts a local adaptive processing and significantly enhances the image contrast and color information while ascertaining good perceptual quality. When compared with the existing enhancement techniques such as adaptive histogram equalization, gamma correction, single-scale retinex, multi-scale retinex, modified high-pass filtering, multi-contrast enhancement, multi-contrast enhancement with dynamic range compression, color enhancement by scaling, edge-preserving multi-scale decomposition and automatic controls of popular imaging tool, the proposed technique gives remarkable performance in terms of relative contrast enhancement, colorfulness and visual quality of enhanced image.

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Citations
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Journal ArticleDOI

Contrast enhancement of dark images using stochastic resonance

TL;DR: In this paper, two stochastic resonance (SR)-based techniques are introduced for enhancement of very low-contrast images, and an expression for optimum noise standard deviation σoptimum that maximises signal-to-noise ratio (SNR) is derived.
Journal ArticleDOI

Bat optimization based neuron model of stochastic resonance for the enhancement of MR images

TL;DR: The proposed modified neuron model based stochastic resonance approach applied for the enhancement of T1 weighted, T2 weighted, fluid-attenuated inversion recovery (FLAIR) and diffusion-weighted imaging (DWI) sequences of magnetic resonance imaging performs well and has been found helpful in the better diagnosis of MR images.
Journal ArticleDOI

Real-time underwater image enhancement: An improved approach for imaging with AUV-150

TL;DR: Suitability of the proposed RGB YCbCr Processing method is validated by real-time implementation during the testing of the Autonomous Underwater Vehicle (AUV-150) developed indigenously by CSIR-CMERI.
Journal ArticleDOI

Perceptual Enhancement of Low Light Images Based on Two-Step Noise Suppression

TL;DR: Experimental results show that the proposed method perceptually enhances contrast in low-light images while successfully minimizing distortions and preserving details, and performs perceptual noise suppression using the JND model.
Proceedings ArticleDOI

Robust contrast enhancement of noisy low-light images: Denoising-enhancement-completion

TL;DR: Experimental results show that the proposed denoising-enhancement-completion algorithm removes noise and enhances the contrast of low-light images more effectively than conventional algorithms.
References
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Journal ArticleDOI

Enhancement of feature extraction for low-quality fingerprint images using stochastic resonance

TL;DR: Experimental results show that Gaussian noise added to low-quality fingerprint images enables the extraction of useful features for biometric identification by adding noise to the original signal.
Journal ArticleDOI

Noise-induced contrast enhancement using stochastic resonance on singular values

TL;DR: The proposed DSR-SVD technique is found to give noteworthy better performance in terms of contrast enhancement factor, color enhancement factor and perceptual quality measure.
Journal ArticleDOI

Enhancement of ultrasound images using stochastic resonance-based wavelet transform.

TL;DR: A technique using stochastic resonance (SR)-based wavelet transform for the enhancement of unclear diagnostic ultrasound images that enhances the edges more clearly and can also optimally enhance an image even if the image noise level is considerable.
Proceedings ArticleDOI

A SR-based radon transform to extract weak lines from noise images

TL;DR: A SR-based Radon transform is presented, in which a bistable stochastic resonance structure is introduced into theRadon transform, which can easily extract weak lines from noise images and give applications in the bearing-time record and the LOFAR display.
Proceedings ArticleDOI

Image enhancement using stochastic resonance [sonar image processing applications]

TL;DR: The results show that the proposed method is suitable for noisy images with very low signal-to-noise ratio (SNR), when the texture of the object is not subtle, and the region where the object lies in is not too small compared to the minimal region coverage over which SR works.
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