Digital image processing (2nd ed.)
Digital image processing (2nd ed.)
A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Independent component analysis, a new concept?
Signal Processing - Special issue on higher order statistics
Self-organizing maps
Nonlinear component analysis as a kernel eigenvalue problem
Neural Computation
Unsupervised classification with non-Gaussian mixture models using ICA
Proceedings of the 1998 conference on Advances in neural information processing systems II
Kernel PCA and de-noising in feature spaces
Proceedings of the 1998 conference on Advances in neural information processing systems II
Independent component analysis: algorithms and applications
Neural Networks
Independent component analysis for noisy data: MEG data analysis
Neural Networks
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Building Nonlinear Data Models with Self-Organizing Maps
ICANN 96 Proceedings of the 1996 International Conference on Artificial Neural Networks
Source separation in post-nonlinear mixtures
IEEE Transactions on Signal Processing
General approach to blind source separation
IEEE Transactions on Signal Processing
Wavelet shrinkage and generalized cross validation for image denoising
IEEE Transactions on Image Processing
Topology preservation in self-organizing feature maps: exact definition and measurement
IEEE Transactions on Neural Networks
Input space versus feature space in kernel-based methods
IEEE Transactions on Neural Networks
Nonlinear blind source separation using a radial basis function network
IEEE Transactions on Neural Networks
An introduction to kernel-based learning algorithms
IEEE Transactions on Neural Networks
Neural network based audio signal denoising
ICAIT '08 Proceedings of the 2008 International Conference on Advanced Infocomm Technology
Integrating Nonlinear Independent Component Analysis and Neural Network in Stock Price Prediction
IEA/AIE '09 Proceedings of the 22nd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems: Next-Generation Applied Intelligence
Learning localisation based on landmarks using self-organisation
ICANN/ICONIP'03 Proceedings of the 2003 joint international conference on Artificial neural networks and neural information processing
Expert Systems with Applications: An International Journal
Image invariant robot navigation based on self organising neural place codes
Biomimetic Neural Learning for Intelligent Robots
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This paper proposes the use of self-organizing maps (SOMs) to the blind source separation (BSS) problem for nonlinearly mixed signals corrupted with multiplicative noise. After an overview of some signal denoising approaches, we introduce the generic independent component analysis (ICA) framework, followed by a survey of existing neural solutions on ICA and nonlinear ICA (NLICA). We then detail a BSS method based on SOMs and intended for image denoising applications. Considering that the pixel intensities of raw images represent a useful signal corrupted with noise, we show that an NLICA-based approach can provide a satisfactory solution to the nonlinear BSS (NLBSS) problem. Furthermore, a comparison between the standard SOM and a modified version, more suitable for dealing with multiplicative noise, is made. Separation results obtained from test and real images demonstrate the feasibility of our approach.