CVPR
2012
IEEE
11 years 6 months ago
2012
IEEE
A large number of problems in computer vision can be modeled as energy minimization problems in a markov random field (MRF) framework. Many methods have been developed over the y...
CVPR
2012
IEEE
11 years 6 months ago
2012
IEEE
While Boltzmann Machines have been successful at unsupervised learning and density modeling of images and speech data, they can be very sensitive to noise in the data. In this pap...
CVPR
2012
IEEE
11 years 6 months ago
2012
IEEE
Image denoising can be described as the problem of mapping from a noisy image to a noise-free image. The best currently available denoising methods approximate this mapping with c...
IJCV
2011
12 years 7 months ago
2011
We examine the underlying structure of popular algorithms for variational methods used in image processing. We focus here on operator splittings and Bregman methods based on a uni...
Publication
This paper presents a computer-aided approach to enhancing suspicious lesions in digital mammograms. The developed algorithm improves on a well-known preprocessor filter named cont...
NIPS
2008
13 years 5 months ago
2008
We present an approach to low-level vision that combines two main ideas: the use of convolutional networks as an image processing architecture and an unsupervised learning procedu...
ICVGIP
2008
13 years 5 months ago
2008
A novel nonlinear cooperative approach to image denoising and restoration is presented. Samples from the image field with similar characteristics are first grouped into clusters b...
ESIAT
2009
IEEE
13 years 7 months ago
2009
IEEE
—In all methods of image denoising, there is a problem always exists that is how to distinguish noise and edge. Now wavelet and contourlet are main tools in image denoising, but ...
ICIP
2000
IEEE
13 years 8 months ago
2000
IEEE
Wavelet-domain hidden Markov models (HMMs) have been recently proposed and applied to image processing, e.g., image denoising. In this paper, we develop a new HMM, called local co...
ICIP
2002
IEEE
13 years 9 months ago
2002
IEEE
—The essence of fractal image denoising is to predict the fractal code of a noiseless image from its noisy observation. From the predicted fractal code, one can generate an estim...