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Nearest-neighbor and bilinear resampling factor estimation to detect blockiness or blurriness of an image

[+] Author Affiliations
Ariawan Suwendi

Xerox Corporation, 800 Phillips Road, Webster, New York 14580

Jan P. Allebach

Purdue University, 1285 Northwestern Avenue, West Lafayette, Indiana 47907

J. Electron. Imaging. 17(2), 023005 (June 05, 2008). doi:10.1117/1.2912053
History: Received November 09, 2006; Revised September 26, 2007; Accepted October 30, 2007; Published June 05, 2008
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In digital publishing, a low-resolution image is highly undesirable. Inexperienced users often try to include low-resolution images from the Internet or digital cameras in documents they are composing. Current preflight tools are able to single them out, but what if those low-resolution images have been interpolated? They may have a sufficient resolution, but their quality has been compromised, especially images interpolated by nearest-neighbor (which includes pixel replication) and bilinear interpolation. The interpolated images often display blocky artifacts, blurry artifacts, or loss of texture. We outline novel nearest-neighbor and bilinear interpolation detection algorithms that are designed to estimate rational resampling factors (above 1×) in both the vertical and horizontal dimensions. The robustness of these algorithms to several common postprocessing algorithms is also evaluated.

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© 2008 SPIE and IS&T

Citation

Ariawan Suwendi and Jan P. Allebach
"Nearest-neighbor and bilinear resampling factor estimation to detect blockiness or blurriness of an image", J. Electron. Imaging. 17(2), 023005 (June 05, 2008). ; http://dx.doi.org/10.1117/1.2912053


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