Spatio-temporally adaptive regularization for enhancement of motion compensated wavelet coded video

  • Authors:

  • Junghoon Jung;Hyunjong Ki;Seongwon Lee;Jeongho Shin;Jinyoung Kang;Joonki Paik

  • Affiliations:

  • Image Processing and Intelligent Systems Lab., Department of Image Engineering, Graduate School of Advanced Imaging Science, Multimedia, and Film, Chung-Ang University, Seoul, Korea;Image Processing and Intelligent Systems Lab., Department of Image Engineering, Graduate School of Advanced Imaging Science, Multimedia, and Film, Chung-Ang University, Seoul, Korea;Image Processing and Intelligent Systems Lab., Department of Image Engineering, Graduate School of Advanced Imaging Science, Multimedia, and Film, Chung-Ang University, Seoul, Korea;Image Processing and Intelligent Systems Lab., Department of Image Engineering, Graduate School of Advanced Imaging Science, Multimedia, and Film, Chung-Ang University, Seoul, Korea;Image Processing and Intelligent Systems Lab., Department of Image Engineering, Graduate School of Advanced Imaging Science, Multimedia, and Film, Chung-Ang University, Seoul, Korea;Image Processing and Intelligent Systems Lab., Department of Image Engineering, Graduate School of Advanced Imaging Science, Multimedia, and Film, Chung-Ang University, Seoul, Korea

  • Venue:
  • PCM'04 Proceedings of the 5th Pacific Rim conference on Advances in Multimedia Information Processing - Volume Part III
  • Year:
  • 2004

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Abstract

The three-dimensional (3D) wavelet transform with motion compensation is a promising video coding algorithm with very high compression rate because of its spatial and temporal decorrelation. However, it still suffers from image degradation such as ringing artifats due to the loss of high frequency components by quantization. In this paper, we present an iterative regularized enhancement of the motion-compensated 3D wavelet coded video. The enhancement includes the adaptive implementation of the constraints for the regularization by selectively suppressing the noise along with the corresponding edge direction. The proposed algorithm efficiently reconstructs images defected by the three-dimensional wavelet transform.