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: Editorial Super-Resolution Imaging: Analysis, Algorithms, and Applications | Hindawi Publishing Corporation EURASIP Journal on Applied Signal Processing Volume 2006 Article ID 90531 Pages 1-2 DOI ASP 2006 90531 Editorial Super-Resolution Imaging Analysis Algorithms and Applications Michael Ng 1 Tony Chan 2 Moon Gi Kang 3 and Peyman Milanfar4 1 Department of Mathematics Hong Kong Baptist University Kowloon Tong Hong Kong 2 Department of Mathematics University of California Los Angeles CA 90095-1555 USA 3 Department of Electrical and Electronic Engineering Yonsei University Seoul 120-749 Korea 4 Department of Electrical Engineering University of California Santa Cruz CA 95064 USA Received 2 August 2005 Accepted 2 August 2005 Copyright 2006 Michael Ng 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. The recent increase in the widespread use of digital imaging technologies in consumer . digital video and other markets . security and military has brought with it a simultaneous demand for higher-resolution HR images. The demand for such images can be partially met by algorithmic advances in super-resolution SR technology in addition to hardware development. Such HR images not only give the viewer a more pleasing picture but also offer additional details that are important for subsequent analysis in many applications. The current hardware approach to obtain HR images mainly relies on sensor manufacturing technology that attempts to increase the number of pixels per unit area by reducing the pixel size. However the cost for high-precision optics and sensors may be prohibitive for general purpose commercial applications and there is a limitation to pixel size reduction due to shot noise encountered in the sensor itself. Therefore a resolution enhancement SR approach using computational mathematical and statistical techniques has received a great deal of attention .
