Efficient image enhancement using sparse source separation in the Retinex theory

Jongsu Yoon, Jangwon Choi, Yoonsik Choe

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)


Color constancy is the feature of the human vision system (HVS) that ensures the relative constancy of the perceived color of objects under varying illumination conditions. The Retinex theory of machine vision systems is based on the HVS. Among Retinex algorithms, the physics-based algorithms are efficient; however, they generally do not satisfy the local characteristics of the original Retinex theory because they eliminate global illumination from their optimization. We apply the sparse source separation technique to the Retinex theory to present a physics-based algorithm that satisfies the locality characteristic of the original Retinex theory. Previous Retinex algorithms have limited use in image enhancement because the total variation Retinex results in an overly enhanced image and the sparse source separation Retinex cannot completely restore the original image. In contrast, our proposed method preserves the image edge and can very nearly replicate the original image without any special operation.

Original languageEnglish
Article number113103
JournalOptical Engineering
Issue number11
Publication statusPublished - 2017 Nov 1

Bibliographical note

Funding Information:
This work was supported by the Technology Innovation Program (No. 10073229, The Industrial Core Technology Development in Robotics) funded by the Ministry of Trade, Industry and Energy (MOTIE, Republic of Korea).

Publisher Copyright:
© 2017 Society of Photo-Optical Instrumentation Engineers (SPIE).

All Science Journal Classification (ASJC) codes

  • Atomic and Molecular Physics, and Optics
  • Engineering(all)


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