8 November 2017 Efficient image enhancement using sparse source separation in the Retinex theory
Author Affiliations +
Abstract
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.
© 2017 Society of Photo-Optical Instrumentation Engineers (SPIE)
Jongsu Yoon, Jongsu Yoon, Jangwon Choi, Jangwon Choi, Yoonsik Choe, Yoonsik Choe, } "Efficient image enhancement using sparse source separation in the Retinex theory," Optical Engineering 56(11), 113103 (8 November 2017). https://doi.org/10.1117/1.OE.56.11.113103 . Submission: Received: 22 July 2017; Accepted: 12 October 2017
Received: 22 July 2017; Accepted: 12 October 2017; Published: 8 November 2017
JOURNAL ARTICLE
9 PAGES


SHARE
Back to Top