Three Novel Models of Threshold Estimator for Wavelet Coefficients
WAA '01 Proceedings of the Second International Conference on Wavelet Analysis and Its Applications
Journal of Mathematical Imaging and Vision
Training methods for image noise level estimation on wavelet components
EURASIP Journal on Applied Signal Processing
ENO adaptive method for solving one-dimensional conservation laws
Applied Numerical Mathematics
IEEE Transactions on Image Processing
Wavelet-based algorithm for attenuation of spatially correlated noise
MUSP'10 Proceedings of the 10th WSEAS international conference on Multimedia systems & signal processing
A robust and fast non-local means algorithm for image denoising
Journal of Computer Science and Technology
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Denoising algorithms based on wavelet thresholding replace small wavelet coefficients by zero and keep or shrink the coefficients with absolute value above the threshold. The optimal threshold minimizes the error of the result as compared to the unknown, exact data. To estimate this optimal threshold, we use generalized cross validation. This procedure does not require an estimation for the noise energy. Originally, this method assumes uncorrelated noise. In this paper, we describe how we can extend it to images with correlated noise