27 January 2009 Image blur estimation based on the average cone of ratio in the wavelet domain
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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.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ljiljana Ilić, Ljiljana Ilić, Aleksandra Pižurica, Aleksandra Pižurica, Ewout Vansteenkiste, Ewout Vansteenkiste, Wilfried Philips, Wilfried Philips, } "Image blur estimation based on the average cone of ratio in the wavelet domain", Proc. SPIE 7248, Wavelet Applications in Industrial Processing VI, 72480F (27 January 2009); doi: 10.1117/12.807412; https://doi.org/10.1117/12.807412


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