Stochastic Resonance AD Conversion and its Effect on Image Enhancement.
ABSTRACT Stochastic resonance (SR) is getting more and more attention in recent few years, as a tool when using noise to enhance system performance. This paper applies SR in the image quantization and presents two types of SR Analog-to-Digital Converter (SR-ADC). One is conventional array SR structured, and another is more efficient by definition of transformation function. It is discovered in the image quantization that the resulting image of SR-ADC has a special visual impression. The image-enhancing performance of SR-ADC is also analyzed. And the low signal-to-noise ratio (SNR) image is enhanced effectively in non-Gaussian noises.
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ABSTRACT: We present an analysis of the exploitation of noise for signal reconstruction by an array of nonlinear threshold-based devices. This phenomenon has been described as a form of stochastic resonance known as suprathreshold stochastic resonance. It occurs when all devices in an array of size N have identical thresholds and are subject to independent additive noise. The original work showed that the mutual information between the input and output of the array has a maximum for a nonzero value of noise intensity, for a random input signal. In this paper, we extend the results on this phenomenon to the case of Laplacian signal and noise probability densities, and show conditions exist under which it is optimal.Acoustics, Speech, and Signal Processing, 2004. Proceedings. (ICASSP '04). IEEE International Conference on; 06/2004
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ABSTRACT: An optimally tuned power-law sensor is shown capable of amplifying the signal-to-noise ratio of a sine wave in Gaussian white noise. When associated in parallel arrays, further improvement can be obtained with independent noises injected on these sensors. This form of stochastic resonance in arrays, obtained here with smooth threshold-free nonlinearities, yields signal-to-noise ratio gains above unity in a true regime of added noise for a sine wave in Gaussian white noise, along with a class of nonlinear devices with useful potentialities for noise-aided information processing.Physical Review E 01/2005; 70(6 Pt 1):060101. · 2.31 Impact Factor
Article: Dithered quantizers[Show abstract] [Hide abstract]
ABSTRACT: A theory of overall quantization noise for nonsubtractive dither was originally developed in unpublished work by J.N. Wright and by T.J. Stockham and subsequently expanded by L.K. Brinton, S.P. Lipshitz, J. Vanderkooy, and R.A. Wannamaker. It is suggested that since these latter results are not as well known as the original results, misunderstanding persists in the literature. New proofs of the properties of quantizer dither, both subtractive and nonsubtractive, are provided. The new proofs are based on elementary Fourier series and Rice's characteristic function method and do not require the use of generalized functions (impulse trains of Dirac delta functions) and sampling theorem arguments. The goal is to provide a unified derivation and presentation of the two forms of dithered quantizer noise based on elementary Fourier techniquesIEEE Transactions on Information Theory 06/1993; · 2.62 Impact Factor