Image deconvolution ringing artifact detection and removal via PSF frequency analysis

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Abstract

We present a new method to detect and remove ringing artifacts produced by the deconvolution process in image deblurring techniques. The method takes into account non-invertible frequency components of the blur kernel used in the deconvolution. Efficient Gabor wavelets are produced for each non-invertible frequency and applied on the deblurred image to generate a set of filter responses that reveal existing ringing artifacts. The set of Gabor filters is then employed in a regularization scheme to remove the corresponding artifacts from the deblurred image. The regularization scheme minimizes the responses of the reconstructed image to these Gabor filters through an alternating algorithm in order to suppress the artifacts. As a result of these steps we are able to significantly enhance the quality of the deblurred images produced by deconvolution algorithms. Our numerical evaluations using a ringing artifact metric indicate the effectiveness of the proposed deringing method. © 2014 Springer International Publishing.

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Mosleh, A., Langlois, J. M. P., & Green, P. (2014). Image deconvolution ringing artifact detection and removal via PSF frequency analysis. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8692 LNCS, pp. 247–262). Springer Verlag. https://doi.org/10.1007/978-3-319-10593-2_17

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