Bayesian Approach to Wavelet-based Image Processing
نویسندگان
چکیده
We present a new method for the reduction of noise in images, using a wavelet transform. The method relies on two principles. The rst is the characterization of the local function regularity by wavelet coeecients. The second is an a priori, geometrical model for wavelet coeecients. Both are combined in a Bayesian framework, to compute for each wavelet coeecient the probability of being \suu-ciently clean". The manipulation of the wavelet coeecients is consequently based on the obtained probabilities.
منابع مشابه
An Improved Pixon-Based Approach for Image Segmentation
An improved pixon-based method is proposed in this paper for image segmentation. In thisapproach, a wavelet thresholding technique is initially applied on the image to reduce noise and toslightly smooth the image. This technique causes an image not to be oversegmented when the pixonbasedmethod is used. Indeed, the wavelet thresholding, as a pre-processing step, eliminates theunnecessary details...
متن کاملStatistical Wavelet-based Image Denoising using Scale Mixture of Normal Distributions with Adaptive Parameter Estimation
Removing noise from images is a challenging problem in digital image processing. This paper presents an image denoising method based on a maximum a posteriori (MAP) density function estimator, which is implemented in the wavelet domain because of its energy compaction property. The performance of the MAP estimator depends on the proposed model for noise-free wavelet coefficients. Thus in the wa...
متن کاملWavelet-based image estimation: an empirical Bayes approach using Jeffrey's noninformative prior
The sparseness and decorrelation properties of the discrete wavelet transform have been exploited to develop powerful denoising methods. However, most of these methods have free parameters which have to be adjusted or estimated. In this paper, we propose a wavelet-based denoising technique without any free parameters; it is, in this sense, a "universal" method. Our approach uses empirical Bayes...
متن کاملBayesian wavelet-based image estimation using noninformative priors
The sparseness and decorrelation properties of the discrete wavelet transform have been exploited to develop powerful denoising methods. Most schemes use arbitrary thresholding nonlinearities with ad hoc parameters, or employ computationally expensive adaptive procedures. We overcome these de ciencies with a new wavelet-based denoising technique derived from a simple empirical Bayes approach ba...
متن کاملWavelet Bayes Adaptive Image Denoising
The class of natural images that we encounter in our daily life is only a small subset of the set of all possible images. This subset is called an image manifold. The Adaptive Digital Image Processing applications are becoming increasingly important and they all start with a mathematical representation of the image. In Bayesian restoration methods, the image manifold is encoded in the form of p...
متن کامل