We present a novel framework for automatic Illumination and Color Compensation algorithm using Mean shift and the Sigma filter (ICCMS) to restore distorted images taken under the arbitrary lighting conditions. The proposed method is effective for appropriate illumination compensation, vivid color restoration, artifacts suppression, automatic parameter estimation, and low computational cost for HW implementation. We show the efficiency of the mean shift filter and sigma filter for illumination compensation with small sized kernel while considering the processing time and removing the artifacts such as HALO and noise amplification. The proposed color restoration function can restore the natural color and correct color noise artifact more perceptually compared with conventional methods. For the automatic processing, the image statistics analysis estimates suitable parameter and all constants are pre-defined. We also introduce the ROI-based parameter estimation dealing with small shadow area against spacious well-exposed background in an image for the touch-screen camera. The object evaluation is performed by CMC, CIEde2000, PSNR, SSIM, and 3D CIELAB gamut with state-of-the-art research and existing commercial solutions.
Bibliographical noteFunding Information:
1This work was supported by the Korea Science and Engineering Foundation (KOSEF) through the Biometrics Engineering Research Center (BERC) at Yonsei University. (R112002105070030(2008)) Heechul Han is with school of electrical and electronic, University of Yonsei, Shinchon-dong, Seoul, and DMC R&D Center, Samsung Electronics, Maetan-3-dong, Suwon, South Korea (e-mail: email@example.com) Kwanghoon Sohn is with school of electrical and electronic, University of Yonsei, Shinchon-dong, Seoul, South Korea (e-mail: firstname.lastname@example.org) Original manuscript received May 28, 2009 Revised manuscript received June 19, 2009
All Science Journal Classification (ASJC) codes
- Media Technology
- Electrical and Electronic Engineering