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JMLR
2010
147views more  JMLR 2010»
12 years 11 months ago
Image Denoising with Kernels Based on Natural Image Relations
A successful class of image denoising methods is based on Bayesian approaches working in wavelet representations. The performance of these methods improves when relations among th...
Valero Laparra, Juan Gutierrez, Gustavo Camps-Vall...
SCALESPACE
2007
Springer
13 years 10 months ago
Uniform and Textured Regions Separation in Natural Images Towards MPM Adaptive Denoising
Abstract. Natural images consist of texture, structure and smooth regions and this makes the task of filtering challenging mainly when it aims at edge and texture preservation. In...
Noura Azzabou, Nikos Paragios, Frederic Guichard
CORR
2010
Springer
109views Education» more  CORR 2010»
12 years 11 months ago
Edge Preserving Image Denoising in Reproducing Kernel Hilbert Spaces
The goal of this paper is the development of a novel approach for the problem of Noise Removal, based on the theory of Reproducing Kernels Hilbert Spaces (RKHS). The problem is ca...
Pantelis Bouboulis, Sergios Theodoridis
NIPS
2008
13 years 6 months ago
Natural Image Denoising with Convolutional Networks
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...
Viren Jain, H. Sebastian Seung
WSCG
2004
166views more  WSCG 2004»
13 years 6 months ago
De-noising and Recovering Images Based on Kernel PCA Theory
Principal Component Analysis (PCA) is a basis transformation to diagonalize an estimate of the covariance matrix of input data and, the new coordinates in the Eigenvector basis ar...
Pengcheng Xi, Tao Xu