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24 October 2005 Automatic focus quality analysis for managing large collection of digital photographs
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Proceedings Volume 6015, Multimedia Systems and Applications VIII; 601510 (2005)
Event: Optics East 2005, 2005, Boston, MA, United States
In managing large collections of digital photographs, there have been many research efforts to compute low level image features such as texture and color to aid different managing tasks (e.g. query-by-example applications or scene classification for image clustering). In this paper, we focus on the assessment of image quality as a complementary feature to improve the manageability of images. Specifically, we propose an effective and efficient algorithm to analyze the focus quality of the photographs and provide quantitative measurement of the assessment. In this algorithm, global figure-of-merits are computed from matrices of the local image statistics such as sharpness, brightness and color saturation. The global figure-of-merits represent how well each image meets the prior assumptions about focus quality of natural images. Then, a collection of the global figure-of-merits are used to decide how well-focused an image is. Experimental results show that the method can detect 90% of the out-of-focus photographs labeled by experts while producing 11% of false positives. We further apply this quantitative measure in image management tasks, including image content filtering/sorting based on the focus quality and image retrieval.
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Suk Hwan Lim, Jonathan Yen, and Peng Wu "Automatic focus quality analysis for managing large collection of digital photographs", Proc. SPIE 6015, Multimedia Systems and Applications VIII, 601510 (24 October 2005);


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