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Proceedings Paper

Image blur estimation based on the average cone of ratio in the wavelet domain
Author(s): Ljiljana Ilić; Aleksandra Pižurica; Ewout Vansteenkiste; Wilfried Philips
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Paper Abstract

In this paper, we propose a new algorithm for objective blur estimation using wavelet decomposition. The central idea of our method is to estimate blur as a function of the center of gravity of the average cone ratio (ACR) histogram. The key properties of ACR are twofold: it is powerful in estimating local edge regularity, and it is nearly insensitive to noise. We use these properties to estimate the blurriness of the image, irrespective of the level of noise. In particular, the center of gravity of the ACR histogram is a blur metric. The method is applicable both in case where the reference image is available and when there is no reference. The results demonstrate a consistent performance of the proposed metric for a wide class of natural images and in a wide range of out of focus blurriness. Moreover, the proposed method shows a remarkable insensitivity to noise compared to other wavelet domain methods.

Paper Details

Date Published: 28 January 2009
PDF: 10 pages
Proc. SPIE 7248, Wavelet Applications in Industrial Processing VI, 72480F (28 January 2009); doi: 10.1117/12.807412
Show Author Affiliations
Ljiljana Ilić, Ghent Univ. (Belgium)
Aleksandra Pižurica, Ghent Univ. (Belgium)
Ewout Vansteenkiste, Ghent Univ. (Belgium)
Wilfried Philips, Ghent Univ. (Belgium)


Published in SPIE Proceedings Vol. 7248:
Wavelet Applications in Industrial Processing VI
Frederic Truchetet; Olivier Laligant, Editor(s)

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