Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Video Enhancement from Multiple Compressed Copies in Transform Domain | Hindawi Publishing Corporation EURASIP Journal on Image and Video Processing Volume 2010 Article ID 404137 18 pages doi 2010 404137 Research Article Video Enhancement from Multiple Compressed Copies in Transform Domain Viet Anh Nguyen 1 Zhenzhong Chen 2 and Yap-Peng Tan2 1 Division of Information Engineering School of Electrical and Electronic Engineering Nanyang Technological University Block S2 Nanyang Avenue Singapore 639798 2 School of Electrical and Electronic Engineering Nanyang Technological University Singapore Correspondence should be addressed to Viet Anh Nguyen vanguyen@ Received 1 May 2010 Revised 22 July 2010 Accepted 24 September 2010 Academic Editor Lei Zhang Copyright 2010 Viet Anh Nguyen et al. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. Increasingly we can obtain more than one compressed copy of the same video content with different levels of visual quality over the Internet. As the original source video is not always available how to choose or derive a video of the best quality from these copies becomes a challenging and interesting problem. In this paper we address this new research problem by blindly enhancing the quality of the video reconstructed from such multiple compressed copies. The aim is to reconstruct a video that achieves a better quality than any of the available copies. Specifically we propose to reconstruct each coefficient of the video in the transform domain by using a narrow quantization constraint set derived from the multiple compressed copies together using a Laplacian or Cauchy distribution model for each AC transform coefficient to minimize the distortion. Analytical and experimental results show the effectiveness of the proposed method. 1. Introduction Over the past few decades transform-based coding has been widely used in lossy image and
