Paper Info
Title
Sharpness estimation for document and scene images
Abstract
Images of document pages have different characteristics than images of natural scenes, and so the sharpness measures developed for natural scene images do not necessarily extend to document images primarily composed of text. We present an efficient and simple method for effectively estimating the sharp-ness/blurriness of document images that also performs well on natural scenes. Our method can be used to predict the sharpness in scenarios where images are blurred due to camera-motion (or hand-shake), defocus, or inherent properties of the imaging system. The proposed method outperforms the perceptually-based, no-reference sharpness work of [1] and [4], which was shown to perform better than 14 other no-reference sharpness measures on the LIVE dataset.
Year
Venue
Keywords
2012
Pattern Recognition
cameras,document image processing,estimation theory,natural scenes,LIVE dataset,camera-motion,document image blurriness,document images sharpness estimation,document pages images,imaging system,natural scene images,no-reference sharpness measures,perceptually-based no-reference sharpness work,scene images
Field
DocType
ISSN
Computer vision,Pattern recognition,Document image processing,Computer science,Artificial intelligence,Estimation theory
Conference
1051-4651
ISBN
Citations 
PageRank 
978-1-4673-2216-4
23
0.95
References 
Authors
7
3
Name
Order
Citations
PageRank
Jayant Kumar117311.11
Francine Chen21218153.96
David Doermann34313312.70