DocumentCode :
63531
Title :
A Regularization Approach to Blind Deblurring and Denoising of QR Barcodes
Author :
van Gennip, Yves ; Athavale, Prashant ; Gilles, Jerome ; Choksi, Rustum
Author_Institution :
Sch. of Math. Sci., Univ. of Nottingham, Nottingham, UK
Volume :
24
Issue :
9
fYear :
2015
fDate :
Sept. 2015
Firstpage :
2864
Lastpage :
2873
Abstract :
QR bar codes are prototypical images for which part of the image is a priori known (required patterns). Open source bar code readers, such as ZBar, are readily available. We exploit both these facts to provide and assess purely regularization-based methods for blind deblurring of QR bar codes in the presence of noise.
Keywords :
QR codes; image denoising; image restoration; QR bar code; ZBar; blind deblurring; blind denoising; open source bar code reader; prototypical image; regularization approach; Bar codes; Cameras; Kernel; Noise; Noise reduction; Standards; TV; QR bar code; TV flow; TV regularization; blind deblurring; finder pattern;
fLanguage :
English
Journal_Title :
Image Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1057-7149
Type :
jour
DOI :
10.1109/TIP.2015.2432675
Filename :
7106501
Link To Document :
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