Blind blur estimation using low rank approximation of cepstrum

    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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