The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Morphological Component Analysis: An Adaptive Thresholding Strategy
Open accessAbstract
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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Cites
Fast Discrete Curvelet Transforms
Candès, E., Demanet, L., Donoho, D., & Ying, L. (2006) · Multiscale Modeling & Simulation · doi:10.1137/05064182x · Cited by 2,573
Self-citationThe transformation of poisson, binomial and negative-binomial data
ANSCOMBE, F. J. (1948) · Biometrika · doi:10.1093/biomet/35.3-4.246 · Cited by 1,300
Metadata
- Authors
- Bobin, J., Starck, J.-L., Fadili, J. M., Moudden, Y., & Donoho, D. L.
- Venue
- IEEE Transactions on Image Processing
- Published
- 2007-11
- Volume
- 16
- Issue
- 11
- Pages
- 2675-2681
- ISSN
- 1057-7149 (ISSN-L)
- OpenAlex
- W2121651107
- Cited by
- 314
- References
- 2
- FWCI
- 14.60
- Type
- journal article
- Language
- en
- Open access
- green
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- Bobin, J., Starck, J.-L., Fadili, J. M., Moudden, Y., & Donoho, D. L. (2007). Morphological Component Analysis: An Adaptive Thresholding Strategy. IEEE Transactions on Image Processing. https://doi.org/10.1109/tip.2007.907073
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