Adaptive Deblurring for Camera-Based Document Image Processing

被引:0
|
作者
Tian, Yibin [1 ]
Ming, Wei [1 ]
机构
[1] Konica Minolta Syst Lab, Foster City, CA 94404 USA
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中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
With increasing resolution of cameras on mobile devices and their computing capacity, camera-based document processing becomes more attractive. However, there are several unique challenges, one of which is defocus. It is common that a camera-captured image is blurred by variable amount of location-dependent defocus. To improve image quality, we developed a novel method to adaptively deblur camera-based document images. In this method, sub-images of interest are first extracted from the captured image, and a point-spread function is derived for each sub-image by analyzing the gradient information along edges. Then the sub-image is deblurred by its local point-spread function. Preliminary experimental results indicate that the proposed adaptive deblurring method significantly improves focusing quality as evaluated by both human observers and objective focus measures compared with single-PSI; deblurring.
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页码:767 / 777
页数:11
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