Paper
11 February 2011 No-reference blur estimation based on the average cone ratio in the wavelet domain
Ljiljana Platisa, Aleksandra Pizurica, Ewout Vansteenkiste, Wilfried Philips
Author Affiliations +
Proceedings Volume 7881, Multimedia on Mobile Devices 2011; and Multimedia Content Access: Algorithms and Systems V; 78811D (2011) https://doi.org/10.1117/12.872836
Event: IS&T/SPIE Electronic Imaging, 2011, San Francisco Airport, California, United States
Abstract
With extensive technological advancements in electronic imaging today, high image quality is becoming an imperative necessity in the modern imaging systems. An important part of quality assurance are techniques for measuring the level of image distortion. Recently, we proposed a wavelet based metric of blurriness in the digital images named CogACR. The metric is highly robust to noise and able to distinguish between a great range of blurriness. Also, it can be used either when the reference degradation-free image is available or when it is unknown. However, the metric is content sensitive and thus in a no-reference scenario it was not fully automated. In this paper, we further investigate this problem. First, we propose a method to classify images based on edge content similarity. Next, we use this method to automate the CogACR estimation of blur in a no-reference scenario. Our results indicate high accuracy of the method 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 method estimates the blur radius with an absolute error of up to 1 pixel in 80 to 90% of the images.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ljiljana Platisa, Aleksandra Pizurica, Ewout Vansteenkiste, and Wilfried Philips "No-reference blur estimation based on the average cone ratio in the wavelet domain", Proc. SPIE 7881, Multimedia on Mobile Devices 2011; and Multimedia Content Access: Algorithms and Systems V, 78811D (11 February 2011); https://doi.org/10.1117/12.872836
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KEYWORDS
Associative arrays

Image quality

Wavelets

Databases

Error analysis

Distortion

Digital imaging

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