Document Type

Journal Article

Department/Unit

Department of Mathematics

Title

Retinex image enhancement via a learned dictionary

Language

English

Abstract

© Society of Photo-Optical Instrumentation Engineers.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.

Keywords

Image enhancement, Learned dictionaries, Retinex, Sparse and redundant representations, Total variation

Publication Date

2015

Source Publication Title

Optical Engineering

Volume

54

Issue

1

Publisher

Society of Photo-optical Instrumentation Engineers

DOI

10.1117/1.OE.54.1.013107

Link to Publisher's Edition

http://dx.doi.org/10.1117/1.OE.54.1.013107

ISSN (print)

00913286

ISSN (electronic)

15602303

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