We consider the estimation of the variance of an additive white Gaussian noise corrupting an image. In the proposed approach, we exploit the nonlocal self-similarity of images to achieve an improved separation of noise and signal. In particular, we utilize the same adaptive 3-D transform decompo...
Noise variance estimation in nonlocal transform domainWe consider the estimation of the variance of an additive white Gaussian noise corrupting an image.2009 International Workshop on Local and Non-Local Approximation in Image Processing (LNLA 2009): Tuusula, Finland 19-21 August 2009...
[21] find that the plain CNN model can compete with BM3D in removing additive white Gaussian noise (AWGN). DnCNN [8] improves the denoising performance by introducing residual learning. One limitation of those methods is that they do not generalize well on different noise types, thus the ...
Optimal detection of a known FSK-modulated binary signal in additive white Gaussian noise using a matched filter receiver requires knowledge of second-order noise statistics. The dependence on noise statistics causes the probability of detection to be sensitive to errors in the noise variance value. ...
The impulsive noise channel is blamed to be the culprit of signal impairment and causes severe performance degradation to modern SCCC which traditionally has been designed to perform optimally in additive white Gaussian noise (AWGN) channel. Undoubtedly, it is a major limiting factors for systems ...
While both of the above algorithms assumed the additive white Gaussian noise model, a recent method by Yao et al. [115] was designed to work with intensity-dependent noise (similar to PRNU). The authors discuss a noise level function (NLF) which aims to better fit noise characteristics with...
The valuation of financial derivatives often assumes risk neutrality with respect to the risk-neutral martingale measure, which prevents arbitrage opportunities. However, casual traders may still incur substantial losses when trading at this risk-neutral price, especially when the price has to be paid ...
Minimum variance time-frequency distribution kernels for signals in additive noise. Derives the minimum variance time-frequency distribution kernel for signals in additive circular complex Gaussian white noise processes. Assumption of the... Amin,Moeness,G. - 《IEEE Transactions on Signal Processing》 被...
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[20] estimated noise level by assuming that the smallest standard deviation of a block is equivalent to additive white Gaussian noise. This method is simple but tends to produce overestimation results for small noise cases. Shin et al. [5] split an image into a number of blocks, which were...