A Regularization Approach to Blind Deblurring and Denoising of QR Barcodes
Yves van Gennip, Prashant Athavale, Rustum Choksi · 2014
Using only regularization-based methods, we provide an ansatz-free algorithm for blind de-blurring of QR bar codes in the presence of noise. The algorithm exploits the fact that QR bar codes are prototypical images for which part of the image is a priori known (finder patterns). The method has four steps: (i) denoising of the entire image via a suitably weighted TV flow; (ii) using a priori knowledge of one of the finder corners to apply a higher-order smooth regular-ization to estimate the unknown point spread function (PSF) associated with the blurring; (iii) applying an appropriately regularized deconvolu-tion using the PSF of step (ii); (iv) thresholding the output. We assess our methods via the open source bar code reader software ZBar [1].