Title

Blind Blur Estimation Using Low Rank Approximation Of Cepstrum

Abstract

The quality of image restoration from degraded images is highly dependent upon a reliable estimate of blur. This paper proposes a blind blur estimation technique based on the low rank approximation of cepstrum. The key idea that this paper presents is that the blur functions usually have low ranks when compared with ranks of real images and can be estimated from cepstrum of degraded images. We extend this idea and propose a general framework for estimation of any type of blur. We show that the proposed technique can correctly estimate commonly used blur types both in noiseless and noisy cases. Experimental results for a wide variety of conditions i.e., when images have low resolution, large blur support, and low signal-to-noise ratio, have been presented to validate our proposed method. © Springer-Verlag Berlin Heidelberg 2006.

Publication Date

1-1-2006

Publication Title

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volume

4141 LNCS

Number of Pages

94-103

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1007/11867586_9

Socpus ID

33749671912 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/33749671912

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