Multiplicative noise removal using self-organizing maps

Haritopoulos, Michel and Yin, Hujun and Allinson, Nigel (2001) Multiplicative noise removal using self-organizing maps. In: Independent Component Analysis, 9-12 December 2001.

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Multiplicative noise removal using self-organizing maps
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Abstract

This paper approaches the problem of image denoising from an Independent Component Analysis (ICA) perspective. Considering that the pixels intensity constituting the crude images represents the useful signal corrupted with noise, we show that, a nonlinear ICA-based approach can provide a satisfactory solution to the Non-Linear Blind Source Separation problem (NLBSS). Self-Organizing Maps (SOMs) are well suited for performing this task, due to their nonlinear mapping property. Separation results obtained from test images demonstrate the feasibility of the proposed method.

Item Type:Conference or Workshop Item (Paper)
Additional Information:This paper approaches the problem of image denoising from an Independent Component Analysis (ICA) perspective. Considering that the pixels intensity constituting the crude images represents the useful signal corrupted with noise, we show that, a nonlinear ICA-based approach can provide a satisfactory solution to the Non-Linear Blind Source Separation problem (NLBSS). Self-Organizing Maps (SOMs) are well suited for performing this task, due to their nonlinear mapping property. Separation results obtained from test images demonstrate the feasibility of the proposed method.
Keywords:Multiplicative Noise, Removal Using Self, Organizing Maps
Subjects:G Mathematical and Computer Sciences > G400 Computer Science
Divisions:College of Science > School of Computer Science
ID Code:5023
Deposited By: Tammie Farley
Deposited On:20 Apr 2012 09:05
Last Modified:13 Mar 2013 09:06

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