In this paper, we develop a unified image deblurring framework that consists of both blur kernel estimation and non-blind image deconvolution. For blind kernel estimation, we propose a patch selection procedure and integrate it with a coarse-to-fine kernel estimation algorithm to develop a robust blur kernel estimation algorithm. For the non-blind image deconvolution, we modify the traditional Richardson-Lucy (RL) image restoration algorithm to suppress the notorious ringing artifact in the regions around strong edges. Experimental results on some real blurred images are shown to demonstrate the improved efficiency and image restoration by using the proposed algorithm. © 2011 Springer-Verlag.
CITATION STYLE
Yang, H. L., Chiao, Y. H., Huang, P. H., & Lai, S. H. (2011). Blind image deblurring with modified Richardson-Lucy deconvolution for ringing artifact suppression. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7088 LNCS, pp. 240–251). https://doi.org/10.1007/978-3-642-25346-1_22
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