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IJON
2002

Independent components of natural images under variable compression rate

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Independent components of natural images under variable compression rate
A generalized ICA model allowing overcomplete bases and additive noises in the observables is applied to natural image data. It is well known that such a model produces independent components that resemble simple cells in primary visual cortex or Gabor functions. We adopt a variable-sparsity density on each independent component, given by the mixture of a delta function and a standard Gaussian density. In the experiment, we observe that the aspect ratios of the optimal bases increase with the noise level and the degree of sparsity. The meaning of this phenomenon is discussed.
Akio Utsugi
Added 22 Dec 2010
Updated 22 Dec 2010
Type Journal
Year 2002
Where IJON
Authors Akio Utsugi
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