Bayesian super-resolution of text image sequences from low resolution observations.

被引：7
|
作者：
Cortijo, FJ [1 ]
Villena, S [1 ]
Molina, R [1 ]
Katsaggelos, A [1 ]
机构：
[1] Univ Granada, Dept Ciencias Computac & IA, E-18071 Granada, Spain
来源：
SEVENTH INTERNATIONAL SYMPOSIUM ON SIGNAL PROCESSING AND ITS APPLICATIONS, VOL 1, PROCEEDINGS | 2003年
关键词：
D O I：
10.1109/ISSPA.2003.1224730
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper deals with the problem of reconstructing high-resolution text images from an incomplete set of undersampled, blurred, and noisy images shifted with subpixel displacement. We derive mathematical expressions for the calculation of the maximum a posteriori estimate of the high resolution image and the estimation of the parameters involved in the model. The method is tested on real text images and car plates, examining the impact of blurring and the number of available low resolution images on the final estimate.
引用
收藏
页码：421 / 424
页数：4
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