DocumentCode :
2737405
Title :
A wavelet constrained POCS supperresolution algorithm for high resolution image reconstruction from video sequence
Author :
Bin Tian ; Hsu, Jennfing T. ; Liu, Qiang ; Li, Ching-Chung ; Sclabassi, Robert J. ; Sun, Mingui
Author_Institution :
Dept. of Neurological Surg., Pittsburgh Univ., PA, USA
Volume :
2
fYear :
2003
fDate :
14-17 Dec. 2003
Firstpage :
1266
Abstract :
Research interest in multi-frame supperresolution has risen substantially in recent years. Most methods developed deal with operations working directly in the image domain. This paper presents a wavelet-domain superresolution method based on the projection on to convex set (POCS) technique. An iterative procedure is utilized to extract information hidden in a group of video frames to update the wavelet coefficients. Since these coefficients correspond to the high frequency information in the spatial domain, the extracted fine features from other frames augment the individual low-resolution image to a superresolution image. The effectiveness of the algorithm is demonstrated by experimental results.
Keywords :
image reconstruction; iterative methods; wavelet transforms; image domain; image reconstruction; iterative procedure; projection on to convex set technique; video frames; video sequence; wavelet constrained POCS supperresolution algorithm; wavelet domain superresolution method; Data mining; Frequency; Image reconstruction; Image resolution; Pollution measurement; Signal resolution; Spatial resolution; Strontium; Video sequences; Wavelet coefficients;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks and Signal Processing, 2003. Proceedings of the 2003 International Conference on
Conference_Location :
Nanjing
Print_ISBN :
0-7803-7702-8
Type :
conf
DOI :
10.1109/ICNNSP.2003.1281101
Filename :
1281101
Link To Document :
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