DocumentCode :
2428723
Title :
A blind super-resolution framework considering the sensor PSF
Author :
Wang, Xiaoling ; Liu, Ju ; Yan, Hua ; Li, Yujun
Author_Institution :
Sch. of Inf. Sci. & Eng., Shandong Univ., Jinan
fYear :
2008
fDate :
7-11 June 2008
Firstpage :
99
Lastpage :
103
Abstract :
Blind super-resolution, which incorporates blur identification into super-resolution, has been proposed to restore the degraded image with either partially known or totally unknown blur. In the conventional framework for blind super-resolution, the sensor PSF caused by camera lens/CCD has always been ignored. Therefore, the identified blur and restored HR image are affected by the sensor PSF, especially when the support of identified blur is relatively small. In this paper, we propose a blind super-resolution framework considering the sensor PSF to solve this problem. In the proposed framework, the sensor PSF and the identified external blur are considered separately, and then Error-Parameter-Analysis algorithm is applied to implement the blind super-resolution. Experiments show that the proposed framework can enhance the accuracy of the blur identification and the quality of the restored HR image.
Keywords :
image resolution; image restoration; CCD; HR image; blind super-resolution framework; blur identification; camera lens; degraded image restoration; error-parameter-analysis algorithm; sensor PSF; Cost function; Helium; Image resolution; Image restoration; Image sensors; Mathematical model; Signal processing algorithms; Signal resolution; Spatial resolution; Strontium;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks and Signal Processing, 2008 International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4244-2310-1
Electronic_ISBN :
978-1-4244-2311-8
Type :
conf
DOI :
10.1109/ICNNSP.2008.4590318
Filename :
4590318
Link To Document :
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