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No-reference blur estimation based on the average cone ratio in the wavelet domain

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Abstract
We propose a wavelet based metric of blurriness in the digital images named CogACR – Center of gravity of the Average Cone Ratio. The metric is highly robust to noise and able to distinguish between a great range of blurriness. To automate the CogACR estimation of blur in a no-reference scenario, we introduce a novel method for image classification based on edge content similarity. Our results indicate high accuracy of the CogACR metric for a range of natural scene images distorted with the out-of-focus blur. Within the considered range of blur radius of 0 to 10 pixels, varied in steps of 0.25 pixels, the proposed metric estimates the blur radius with an absolute error of up to 1 pixel in 80 to 90% of the images.
Keywords
image quality, CogACR estimation, edge detection, degradation free image, image restoration, average cone ratio, estimation theory, wavelet transform, blur estimation, electronic imaging, natural scene image, image distortion

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Chicago
Platisa, Ljiljana, Aleksandra Pizurica, Ewout Vansteenkiste, and Wilfried Philips. 2011. “No-reference Blur Estimation Based on the Average Cone Ratio in the Wavelet Domain.” In Quality of Multimedia Experience, 3rd International Workshop, Abstracts.
APA
Platisa, L., Pizurica, A., Vansteenkiste, E., & Philips, W. (2011). No-reference blur estimation based on the average cone ratio in the wavelet domain. Quality of Multimedia Experience, 3rd International workshop, Abstracts. Presented at the 3rd International workshop on Quality of Multimedia Experience (QoMEX - 2011).
Vancouver
1.
Platisa L, Pizurica A, Vansteenkiste E, Philips W. No-reference blur estimation based on the average cone ratio in the wavelet domain. Quality of Multimedia Experience, 3rd International workshop, Abstracts. 2011.
MLA
Platisa, Ljiljana et al. “No-reference Blur Estimation Based on the Average Cone Ratio in the Wavelet Domain.” Quality of Multimedia Experience, 3rd International Workshop, Abstracts. 2011. Print.
@inproceedings{1081506,
  abstract     = {We propose a wavelet based metric of blurriness in the digital images named CogACR – Center of gravity of the Average Cone Ratio. The metric is highly robust to noise and able to distinguish between a great range of blurriness. To automate the CogACR estimation of blur in a no-reference scenario, we introduce a novel method for image classification based on edge content similarity. Our results indicate high accuracy of the CogACR metric for a range of natural scene images distorted with the out-of-focus blur. Within the considered range of blur radius of 0 to 10 pixels, varied in steps of 0.25 pixels, the proposed metric estimates the blur radius with an absolute error of up to 1 pixel in 80 to 90% of the images.},
  author       = {Platisa, Ljiljana and Pizurica, Aleksandra and Vansteenkiste, Ewout and Philips, Wilfried},
  booktitle    = {Quality of Multimedia Experience, 3rd International workshop, Abstracts},
  keywords     = {image quality,CogACR estimation,edge detection,degradation free image,image restoration,average cone ratio,estimation theory,wavelet transform,blur estimation,electronic imaging,natural scene image,image distortion},
  language     = {eng},
  location     = {Mechelen, Belgium},
  title        = {No-reference blur estimation based on the average cone ratio in the wavelet domain},
  year         = {2011},
}