Wavelet shrinkage is an image denoising technique based on the concept of thresholding the wavelet coefficients. The key challenge of wavelet shrinkage is to find an appropriate threshold value, which is typically controlled by the signal variance. To tackle this challenge, a new image shrinkage approach is proposed in this paper by using a variance field diffusion, which can provide more accurate variance estimation. Experimental results are provided to demonstrate the superior performance of the proposed approach. ? 2011 IEEE.EI
This thesis is a contribution to the field equivalences of different methods of mathematical image ...
We study a Bayesian wavelet shrinkage approach for natural images based on a probability that a give...
This contribution describes a method for ideal de-noising. This method is based on a choice of an op...
Wavelet shrinkage is an image restoration technique based on the concept of thresholding the wavelet...
Conference PaperWavelet shrinkage is a signal estimation technique that exploits the remarkable abil...
This paper investigates the statistical characterizationof mul-tiscale wavelet coefficients correspo...
Nonlinear diffusion, proposed by Perona and Malik, is a well-known method for image denoising with e...
Removing noise without sacrificing important structures Nonlinear strategies: Wavelet shrinkage and ...
Abstract. Most two-dimensional methods for wavelet shrinkage are ef-ficient for edge-preserving imag...
In this paper, we propose a context adaptive nonlinear diffusion method for image denoising in wavel...
In this paper, we propose a context adaptive nonlinear diffusion method for image denoising in wavel...
This paper investigates the statistical characterization of multiscale wavelet coefficients corresp...
Image processing is always being a research field for the researcher. The Image denoising is one of ...
A technique to de-noise images, based from the research of Piz urica, Philips, Lemahieu and Acheroy,...
The image data is normally corrupted by additive noise during acquisition. This reduces the accuracy...
This thesis is a contribution to the field equivalences of different methods of mathematical image ...
We study a Bayesian wavelet shrinkage approach for natural images based on a probability that a give...
This contribution describes a method for ideal de-noising. This method is based on a choice of an op...
Wavelet shrinkage is an image restoration technique based on the concept of thresholding the wavelet...
Conference PaperWavelet shrinkage is a signal estimation technique that exploits the remarkable abil...
This paper investigates the statistical characterizationof mul-tiscale wavelet coefficients correspo...
Nonlinear diffusion, proposed by Perona and Malik, is a well-known method for image denoising with e...
Removing noise without sacrificing important structures Nonlinear strategies: Wavelet shrinkage and ...
Abstract. Most two-dimensional methods for wavelet shrinkage are ef-ficient for edge-preserving imag...
In this paper, we propose a context adaptive nonlinear diffusion method for image denoising in wavel...
In this paper, we propose a context adaptive nonlinear diffusion method for image denoising in wavel...
This paper investigates the statistical characterization of multiscale wavelet coefficients corresp...
Image processing is always being a research field for the researcher. The Image denoising is one of ...
A technique to de-noise images, based from the research of Piz urica, Philips, Lemahieu and Acheroy,...
The image data is normally corrupted by additive noise during acquisition. This reduces the accuracy...
This thesis is a contribution to the field equivalences of different methods of mathematical image ...
We study a Bayesian wavelet shrinkage approach for natural images based on a probability that a give...
This contribution describes a method for ideal de-noising. This method is based on a choice of an op...