A Regularization Approach to Blind Deblurring and Denoising of QR Barcodes

A Regularization Approach to Blind Deblurring and Denoising of QR Barcodes

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...

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Veröffentlicht in:IEEE transactions on image processing 2015-09, Vol.24 (9), p.2864-2873
Hauptverfasser: van Gennip, Yves, Athavale, Prashant, Gilles, Jerome, Choksi, Rustum
Format: Artikel
Sprache:eng
Schlagworte:
Bar codes
blind deblurring
Cameras
finder pattern
Kernel
Noise
Noise reduction
QR bar code
TV flow
TV regularization
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container_title IEEE transactions on image processing
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creator van Gennip, Yves
Athavale, Prashant
Gilles, Jerome
Choksi, Rustum
description 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.
doi_str_mv 10.1109/TIP.2015.2432675
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subjects Bar codes
blind deblurring
Cameras
finder pattern
Kernel
Noise
Noise reduction
QR bar code
TV flow
TV regularization
title A Regularization Approach to Blind Deblurring and Denoising of QR Barcodes
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