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IJCV
2011
9 months 2 days 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 uniď...
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
1 years 7 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
1 years 7 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
1 years 8 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
1 years 10 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
1 years 10 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...
ICIAR
2007
Springer
1 years 11 months ago
2007
Springer
Abstract. In this paper we present a novel single-frame image zooming technique based on so-called “self-examples”. Our method combines the ideas of fractal-based image zooming...
ICIAR
2009
Springer
2 years 2 days ago
2009
Springer
Abstract. State-of-the-art image denoising algorithms attempt to recover natural image signals from their noisy observations, such that the statistics of the denoised image follow ...
Source Code
TV-based image restoration with options for deconvolution, inpainting, and different noise models. Chan-Vese segmentation also included. Usable from C, C++, or MATLAB.
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