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Proceedings Paper

No-reference multiscale blur detection tool for content based image retrieval
Author(s): Soundararajan Ezekiel; Russell Stocker; Kyle Harrity; Mark Alford; David Ferris; Erik Blasch; Mark Gorniak
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Paper Abstract

In recent years, digital cameras have been widely used for image capturing. These devices are equipped in cell phones, laptops, tablets, webcams, etc. Image quality is an important component of digital image analysis. To assess image quality for these mobile products, a standard image is required as a reference image. In this case, Root Mean Square Error and Peak Signal to Noise Ratio can be used to measure the quality of the images. However, these methods are not possible if there is no reference image. In our approach, a discrete-wavelet transformation is applied to the blurred image, which decomposes into the approximate image and three detail sub-images, namely horizontal, vertical, and diagonal images. We then focus on noise-measuring the detail images and blur-measuring the approximate image to assess the image quality. We then compute noise mean and noise ratio from the detail images, and blur mean and blur ratio from the approximate image. The Multi-scale Blur Detection (MBD) metric provides both an assessment of the noise and blur content. These values are weighted based on a linear regression against full-reference y values. From these statistics, we can compare to normal useful image statistics for image quality without needing a reference image. We then test the validity of our obtained weights by R2 analysis as well as using them to estimate image quality of an image with a known quality measure. The result shows that our method provides acceptable results for images containing low to mid noise levels and blur content.

Paper Details

Date Published: 19 June 2014
PDF: 8 pages
Proc. SPIE 9089, Geospatial InfoFusion and Video Analytics IV; and Motion Imagery for ISR and Situational Awareness II, 90890I (19 June 2014); doi: 10.1117/12.2058062
Show Author Affiliations
Soundararajan Ezekiel, Indiana Univ. of Pennsylvania (United States)
Russell Stocker, Indiana Univ. of Pennsylvania (United States)
Kyle Harrity, Indiana Univ. of Pennsylvania (United States)
Mark Alford, Air Force Research Lab. (United States)
David Ferris, Air Force Research Lab. (United States)
Erik Blasch, Air Force Research Lab. (United States)
Mark Gorniak, Air Force Research Lab. (United States)


Published in SPIE Proceedings Vol. 9089:
Geospatial InfoFusion and Video Analytics IV; and Motion Imagery for ISR and Situational Awareness II
Matthew F. Pellechia; Kannappan Palaniappan; Shiloh L. Dockstader; Paul B. Deignan; Peter J. Doucette; Donnie Self, Editor(s)

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