Performance analysis of unconventional dictionary on retinal images | IEEE Conference Publication | IEEE Xplore

Performance analysis of unconventional dictionary on retinal images


Abstract:

Signals are sparsely represented by a set of over-complete basis vectors called dictionary. Atoms of a dictionary are either chosen from a predefined set of functions suc...Show More

Abstract:

Signals are sparsely represented by a set of over-complete basis vectors called dictionary. Atoms of a dictionary are either chosen from a predefined set of functions such as Discrete Cosine Transform (DCT), Wavelets, Gabor, Contourlets, and Curvelets or learned from an image itself. Recently, a nonlinear (NL) dictionary has been proposed by adding NL functions to the conventional DCT atoms. This paper presents performance of a novel NL dictionary for retinal image reconstruction and denoising. The NL dictionary demonstrates good performance and can be adapted if shorter execution time is required.
Date of Conference: 27-30 October 2014
Date Added to IEEE Xplore: 29 January 2015
Electronic ISBN:978-1-4799-5751-4

ISSN Information:

Conference Location: Paris, France

References

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