Retinex image enhancement via a learned dictionary

Huibin Chang; Michael K. Ng; Wei Wang; Tieyong Zeng

doi:10.1117/1.OE.54.1.013107

26 January 2015 Retinex image enhancement via a learned dictionary

Huibin Chang, Michael K. Ng, Wei Wang, Tieyong Zeng

Author Affiliations +

Optical Engineering, 54(1), 013107 (2015). https://doi.org/10.1117/1.OE.54.1.013107

Abstract

The main aim of this paper is to study image enhancement by using sparse and redundant representations of the reflectance component in the Retinex model over a learned dictionary. This approach is different from existing variational methods, and the advantage of this approach is that the reflectance component in the Retinex model can be represented with more details by the dictionary. A variational method based on the dynamic dictionaries is adopted here, where it changes with respect to iterations of the enhancement algorithm. Numerical examples are also reported to demonstrate that the proposed methods can provide better visual quality of the enhanced high-contrast images than the other variational methods, i.e., revealing more details in the low-light part.

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Huibin Chang, Huibin Chang, Michael K. Ng, Michael K. Ng, Wei Wang, Wei Wang, Tieyong Zeng, Tieyong Zeng, } "Retinex image enhancement via a learned dictionary," Optical Engineering 54(1), 013107 (26 January 2015). https://doi.org/10.1117/1.OE.54.1.013107 . Submission:

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