Title

Blind blur estimation using low rank approximation of cepstrum

Authors

Authors

A. A. Bhutta;H. Foroosh

Comments

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Keywords

DECONVOLUTION; IMAGE; IDENTIFICATION; Computer Science, Artificial Intelligence; Computer Science, Theory &; Methods

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.

Journal Title

Image Analysis and Recognition, Pt 1

Volume

4141

Publication Date

1-1-2006

Document Type

Article

Language

English

First Page

94

Last Page

103

WOS Identifier

WOS:000241552700009

ISSN

0302-9743; 3-540-44891-8

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