A Regularization Approach to Blind Deblurring and Denoising of QR Barcodes
Yves van Gennip, Prashant Athavale, J\'er\^ome Gilles, Rustum Choksi
TL;DR
This paper introduces a regularization-based method for blind deblurring and denoising of QR barcodes, leveraging known patterns to improve image restoration in noisy conditions.
Contribution
It presents a novel regularization approach specifically designed for QR barcode deblurring and denoising, utilizing prior knowledge of barcode patterns.
Findings
Effective deblurring of QR barcodes demonstrated
Improved noise robustness in barcode restoration
Method outperforms traditional techniques
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.
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