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» Blind separation of convolutive image mixtures
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TSP
2008
166views more  TSP 2008»
13 years 5 months ago
A Convex Analysis Framework for Blind Separation of Non-Negative Sources
This paper presents a new framework for blind source separation (BSS) of non-negative source signals. The proposed framework, referred herein to as convex analysis of mixtures of ...
Tsung-Han Chan, Wing-Kin Ma, Chong-Yung Chi, Yue W...
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
ICA
2004
Springer
13 years 10 months ago
Second-Order Blind Source Separation Based on Multi-dimensional Autocovariances
SOBI is a blind source separation algorithm based on time decorrelation. It uses multiple time autocovariance matrices, and performs joint diagonalization thus being more robust th...
Fabian J. Theis, Anke Meyer-Bäse, Elmar Wolfg...
ICCV
1999
IEEE
14 years 7 months ago
Independent Component Analysis of Textures
The technique of independent component analysis (ICA) is applied for texture feature detection. In ICA an optimal transformation (with respect to the statistical structure of the i...
Roberto Manduchi, Javier Portilla
ESANN
2006
13 years 6 months ago
Non-orthogonal Support Width ICA
Independent Component Analysis (ICA) is a powerful tool with applications in many areas of blind signal processing; however, its key assumption, i.e. the statistical independence o...
John Aldo Lee, Frédéric Vrins, Miche...