Morphological Component Analysis: An Adaptive Thresholding Strategy

descriptionPublicationkeyboard_double_arrow_right Article 01 Nov 2007 France Publisher:Institute of Electrical and Electronics Engineers (IEEE)Journal:IEEE Transactions on Image Processing, volume 16, pages 2,675-2,681 (issn: 1057-7149,

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Authors: Jérôme Bobin; Jean-Luc Starck; Jalal Fadili; Yassir Moudden; David L. Donoho;

doi: 10.1109/tip.2007.907073

pmid: 17990744

Morphological Component Analysis: An Adaptive Thresholding Strategy

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Abstract

In a recent paper, a method called morphological component analysis (MCA) has been proposed to separate the texture from the natural part in images. MCA relies on an iterative thresholding algorithm, using a threshold which decreases linearly towards zero along the iterations. This paper shows how the MCA convergence can be drastically improved using the mutual incoherence of the dictionaries associated to the different components. This modified MCA algorithm is then compared to basis pursuit, and experiments show that MCA and BP solutions are similar in terms of sparsity, as measured by the l1 norm, but MCA is much faster and gives us the possibility of handling large scale data sets.

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France

Related Organizations

University of Paris-Saclay
France
Normandie Université
France
French National Centre for Scientific Research
France
Université de Caen Normandie
France
Stanford University
United States

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Keywords

Principal Component Analysis, [INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing, Reproducibility of Results, sparse representations., Image Enhancement, Sensitivity and Specificity, 510, 620, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, morphological component analysis (MCA), [INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV], Artificial Intelligence, [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV], sparse representations, Image Interpretation, Computer-Assisted, Feature extraction, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, Algorithms, [SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing

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