A Convex Optimization Model and Algorithm for Retinex
| Autor: | Qing-Nan Zhao, Xi-Le Zhao, Ting-Zhu Huang, Ming-Hui Cheng, Tian-Hui Ma |
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| Rok vydání: | 2017 |
| Předmět: |
Article Subject
Color constancy lcsh:Mathematics General Mathematics General Engineering 010103 numerical & computational mathematics 02 engineering and technology Total variation denoising lcsh:QA1-939 01 natural sciences Tikhonov regularization Reflection (mathematics) lcsh:TA1-2040 Component (UML) Convex optimization Human visual system model 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing 0101 mathematics lcsh:Engineering (General). Civil engineering (General) Algorithm Variable (mathematics) Mathematics |
| Zdroj: | Mathematical Problems in Engineering, Vol 2017 (2017) |
| ISSN: | 1563-5147 1024-123X |
| DOI: | 10.1155/2017/4012767 |
| Popis: | Retinex is a theory on simulating and explaining how human visual system perceives colors under different illumination conditions. The main contribution of this paper is to put forward a new convex optimization model for Retinex. Different from existing methods, the main idea is to rewrite a multiplicative form such that the illumination variable and the reflection variable are decoupled in spatial domain. The resulting objective function involves three terms including the Tikhonov regularization of the illumination component, the total variation regularization of the reciprocal of the reflection component, and the data-fitting term among the input image, the illumination component, and the reciprocal of the reflection component. We develop an alternating direction method of multipliers (ADMM) to solve the convex optimization model. Numerical experiments demonstrate the advantages of the proposed model which can decompose an image into the illumination and the reflection components. |
| Databáze: | OpenAIRE |
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