Blind Images Separation Based on Sparse Independent Component Analysis

Jing Hui Wang; Yuan Chao Zhao; Dong Sheng Chen

doi:10.4028/www.scientific.net/AMR.846-847.929

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 846-847Blind Images Separation Based on Sparse...

Blind Images Separation Based on Sparse Independent Component Analysis

Abstract:

In this paper, a novel sparse component multi-resolution independent component analysis is presented. This method separates mixed images based on quadratic function of sparse component coefficient. The quadratic function can be interpreted as the time-frequency function or time-scale function. The performance of the algorithm is evaluated by using noisy mixed images data. Experimental results show that the method is feasible.

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Periodical:

Advanced Materials Research (Volumes 846-847)

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929-933

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https://doi.org/10.4028/www.scientific.net/AMR.846-847.929

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Online since:

November 2013

Authors:

Jing Hui Wang*, Yuan Chao Zhao, Dong Sheng Chen

Keywords:

Image, Independent Component Analysis (ICA), Sparse

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