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Proceedings Article•DOI•

Image denoising using dynamic stochastic resonance in wavelet domain

TL;DR: When compared with the conventional techniques for gaussian denoising, such as gaussian low pass filtering, and soft thresholding of wavelet coefficients, the DSR-based technique is found to give marginally better noise reduction in most of the cases.
Abstract: A dynamic stochastic resonance (DSR)-based technique in discrete wavelet transform (DWT) domain for noise suppression in digital images has been proposed in this paper. The initial results on investigation of this concept for denoising of images corrupted by gaussian noise have been presented. Though traditionally noise is considered as undesirable, it has been utilized in the proposed technique to reduce its own effect. In the iterative DSR step, an input noisy image is subjected to independent noise of different standard deviations that iteratively tunes the detail wavelet coefficients, such that the overall effect is the suppression of the degradation due to its own noise. The results are quantified in terms of Noise Mean Value (NMV), Noise Standard Deviation (NSD), and Mean Square Difference (MSD). When compared with the conventional techniques for gaussian denoising, such as gaussian low pass filtering, and soft thresholding of wavelet coefficients, the DSR-based technique is found to give marginally better noise reduction in most of the cases.
Citations
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Journal Article•DOI•
TL;DR: A novel binary image enhancement scheme based on aperiodic SR (ASR) technique is proposed and simulation results show that the proposed method is superior to the traditionalbinary image enhancement methods both in visual effect and PSNR performance.
Abstract: The enhancement of noisy images has been playing a key role in improving the visual effect and the performance of image processing. Traditional methods for image enhancement are mainly focusing on eliminating noise, which cannot acquire good effect under low peak-signal-to-noise ratio (PSNR) conditions. Stochastic resonance (SR), on the contrary, is a technique using noise to enhance signal. Owing to the unique feature of SR, a novel binary image enhancement scheme based on aperiodic SR (ASR) technique is proposed. In this study, the authors take the improvement in PSNR as a measure of the ASR-based binary image enhancement system, which provides a guideline for the realisation of the ASR system. On this basis, they obtain the PSNR expression of the ASR-based binary image enhancement system. Simulation results show that the proposed method is superior to the traditional binary image enhancement methods both in visual effect and PSNR performance.

21 citations

Journal Article•DOI•
TL;DR: A novel dynamic stochastic resonance (DSR)-based technique for robust extraction of a grayscale logo from a tampered watermarked image and suggests that remarkable improvement of robustness is achieved by using DSR on singular values of DCT.
Abstract: This paper presents a novel dynamic stochastic resonance (DSR)-based technique for robust extraction of a grayscale logo from a tampered watermarked image. The watermark embedding is done on the singular values (SV) of the discrete cosine transform (DCT) coefficients of the cover image. DSR is then strategically applied during the logo extraction process where the SV of DCT coefficients are tuned following a double-well potential model by utilizing the noise introduced during attacks. The resilience of this technique has been tested in the presence of various noises, geometrical distortions, enhancement, compression, filtering and watermarking attacks. The proposed DSR-based technique for logo extraction gives noteworthy robustness without any significant trade-off in perceptual transparency of the watermarked image. A maximization approach has been adopted for the selection of bistable double-well parameters to establish noise-enhanced resonance. When compared with existing watermark extraction techniques based in SVD, DCT, SVD-DCT domains, as well as with their combination with DSR, the results suggest that remarkable improvement of robustness is achieved by using DSR on singular values of DCT.

15 citations

Journal Article•DOI•
11 Nov 2013
TL;DR: A novel technique based on dynamic stochastic resonance in discrete cosine transform (DCT) domain has been proposed in this paper for the enhancement of dark as well as low-contrast images and gives remarkable performance in terms of contrast and color enhancement while ascertaining good perceptual quality.
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.

15 citations

Proceedings Article•DOI•
01 Nov 2018
TL;DR: A significant improvement in sharpness of edges in the denoised images in comparison with the conventional NLM approach both visually and quantitatively in terms of full-reference and no-reference image quality metrics.
Abstract: Noise-aided stochastic resonance has been explored in recent literature as a powerful tool that enhances the performance of non-linear systems, particularly in image enhancement and image watermarking. In this paper, we extend the application of stochastic resonance to improve the performance of the conventional non-local means (NLM) filtering for edge-preserving image denoising. The NLM algorithm typically involves computation of weights denoting similarity of a pixel with all other pixels in the image. In the proposed algorithm, these similarity weights are iteratively processed using the concept of dynamic stochastic resonance. The results indicate a significant improvement in sharpness of edges in the denoised images in comparison with the conventional NLM approach both visually and quantitatively in terms of full-reference and no-reference image quality metrics.

5 citations


Cites methods from "Image denoising using dynamic stoch..."

  • ...SR has been successfully applied in the context of image processing applications such as image enhancement [22, 23, 24], robust watermark extraction [25, 26], and wavelet-based image denoising [27]....

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Journal Article•DOI•
TL;DR: In this article , the authors proposed an indoor and outdoor integrated radiometric calibration method for large-array commodity CMOS multispectral cameras using the lookup table method to correct vignetting effect rather than nonlinear regression.

4 citations

References
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Book Chapter•DOI•

[...]

01 Jan 2012

139,059 citations


"Image denoising using dynamic stoch..." refers background in this paper

  • ...Recently some of the works on application of stochastic resonance for grayscale image denoising or enhancement that have been reported in literature are [3], [4], [5], [6], [7], [8], [9], [10], [11]....

    [...]

Book•
01 Jan 1998
TL;DR: An introduction to a Transient World and an Approximation Tour of Wavelet Packet and Local Cosine Bases.
Abstract: Introduction to a Transient World. Fourier Kingdom. Discrete Revolution. Time Meets Frequency. Frames. Wavelet Zoom. Wavelet Bases. Wavelet Packet and Local Cosine Bases. An Approximation Tour. Estimations are Approximations. Transform Coding. Appendix A: Mathematical Complements. Appendix B: Software Toolboxes.

17,693 citations


"Image denoising using dynamic stoch..." refers methods or result in this paper

  • ...However, in terms of NSD, S2DWT exhibits more efficiency....

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  • ...Many techniques using wavelet-based thresholding have been reported in literature [13], [14], [16], [17], [18]....

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  • ...Graph for MSD shows larger values for DSR-based technique than Gaussian LPF or S2DWT....

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  • ...2, in comparison with results obtained for same amount of added noise using Gaussian low pass filtering (Gaussian LPF), and soft thresholding on separable 2DWT (S2DWT) [17], [21]....

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  • ...Since the focus is in wavelet domain, a comparison has also been made with a conventional denoising method that uses soft thresholding on detail coefficients of separable 2-D discrete wavelet transformation [17]....

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Journal Article•DOI•
David L. Donoho1•
TL;DR: The authors prove two results about this type of estimator that are unprecedented in several ways: with high probability f/spl circ/*/sub n/ is at least as smooth as f, in any of a wide variety of smoothness measures.
Abstract: Donoho and Johnstone (1994) proposed a method for reconstructing an unknown function f on [0,1] from noisy data d/sub i/=f(t/sub i/)+/spl sigma/z/sub i/, i=0, ..., n-1,t/sub i/=i/n, where the z/sub i/ are independent and identically distributed standard Gaussian random variables. The reconstruction f/spl circ/*/sub n/ is defined in the wavelet domain by translating all the empirical wavelet coefficients of d toward 0 by an amount /spl sigma//spl middot//spl radic/(2log (n)/n). The authors prove two results about this type of estimator. [Smooth]: with high probability f/spl circ/*/sub n/ is at least as smooth as f, in any of a wide variety of smoothness measures. [Adapt]: the estimator comes nearly as close in mean square to f as any measurable estimator can come, uniformly over balls in each of two broad scales of smoothness classes. These two properties are unprecedented in several ways. The present proof of these results develops new facts about abstract statistical inference and its connection with an optimal recovery model. >

9,359 citations


"Image denoising using dynamic stoch..." refers methods in this paper

  • ...Many techniques using wavelet-based thresholding have been reported in literature [13], [14], [16], [17], [18]....

    [...]

Journal Article•DOI•
TL;DR: An adaptive, data-driven threshold for image denoising via wavelet soft-thresholding derived in a Bayesian framework, and the prior used on the wavelet coefficients is the generalized Gaussian distribution widely used in image processing applications.
Abstract: The first part of this paper proposes an adaptive, data-driven threshold for image denoising via wavelet soft-thresholding. The threshold is derived in a Bayesian framework, and the prior used on the wavelet coefficients is the generalized Gaussian distribution (GGD) widely used in image processing applications. The proposed threshold is simple and closed-form, and it is adaptive to each subband because it depends on data-driven estimates of the parameters. Experimental results show that the proposed method, called BayesShrink, is typically within 5% of the MSE of the best soft-thresholding benchmark with the image assumed known. It also outperforms SureShrink (Donoho and Johnstone 1994, 1995; Donoho 1995) most of the time. The second part of the paper attempts to further validate claims that lossy compression can be used for denoising. The BayesShrink threshold can aid in the parameter selection of a coder designed with the intention of denoising, and thus achieving simultaneous denoising and compression. Specifically, the zero-zone in the quantization step of compression is analogous to the threshold value in the thresholding function. The remaining coder design parameters are chosen based on a criterion derived from Rissanen's minimum description length (MDL) principle. Experiments show that this compression method does indeed remove noise significantly, especially for large noise power. However, it introduces quantization noise and should be used only if bitrate were an additional concern to denoising.

2,917 citations

Journal Article•DOI•
TL;DR: Li et al. as discussed by the authors presented a new biometric approach to online personal identification using palmprint technology, which consists of two parts: a novel device for online palmprint image acquisition and an efficient algorithm for fast palmprint recognition.
Abstract: —Biometrics-based personal identification is regarded as an effective method for automatically recognizing, with a high confidence, a person's identity. This paper presents a new biometric approach to online personal identification using palmprint technology. In contrast to the existing methods, our online palmprint identification system employs low-resolution palmprint images to achieve effective personal identification. The system consists of two parts: a novel device for online palmprint image acquisition and an efficient algorithm for fast palmprint recognition. A robust image coordinate system is defined to facilitate image alignment for feature extraction. In addition, a 2D Gabor phase encoding scheme is proposed for palmprint feature extraction and representation. The experimental results demonstrate the feasibility of the proposed system.

908 citations