Imaging Components, Systems, and Processing

Retinex image enhancement via a learned dictionary

[+] Author Affiliations
Huibin Chang

Tianjin Normal University, School of Mathematical Sciences, West Binshui Road, Tianjin 300387, China

Michael K. Ng

Hong Kong Baptist University, Institute of Computational and Theoretical Studies, and Department of Mathematics, Kowloon Tong, Hong Kong

Wei Wang

Tongji University, Department of Mathematics, Siping Road, Shanghai 200092, China

Tieyong Zeng

Hong Kong Baptist University, Institute of Computational and Theoretical Studies, and Department of Mathematics, Kowloon Tong, Hong Kong

Opt. Eng. 54(1), 013107 (Jan 26, 2015). doi:10.1117/1.OE.54.1.013107
History: Received June 6, 2014; Accepted December 24, 2014
Text Size: A A A

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.

Figures in this Article
© 2015 Society of Photo-Optical Instrumentation Engineers

Citation

Huibin Chang ; Michael K. Ng ; Wei Wang and Tieyong Zeng
"Retinex image enhancement via a learned dictionary", Opt. Eng. 54(1), 013107 (Jan 26, 2015). ; http://dx.doi.org/10.1117/1.OE.54.1.013107


Tables

Access This Article
Sign in or Create a personal account to Buy this article ($20 for members, $25 for non-members).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging & repositioning the boxes below.

Related Book Chapters

Topic Collections

Advertisement


 

  • Don't have an account?
  • Subscribe to the SPIE Digital Library
  • Create a FREE account to sign up for Digital Library content alerts and gain access to institutional subscriptions remotely.
Access This Article
Sign in or Create a personal account to Buy this article ($20 for members, $25 for non-members).
Access This Proceeding
Sign in or Create a personal account to Buy this article ($15 for members, $18 for non-members).
Access This Chapter

Access to SPIE eBooks is limited to subscribing institutions and is not available as part of a personal subscription. Print or electronic versions of individual SPIE books may be purchased via SPIE.org.