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

Ariawan Suwendi; Jan P. Allebach

doi:10.1117/1.2912053

1 April 2008 Nearest-neighbor and bilinear resampling factor estimation to detect blockiness or blurriness of an image

Ariawan Suwendi, Jan P. Allebach

Author Affiliations +

Journal of Electronic Imaging, Vol. 17, Issue 2, 023005 (April 2008). https://doi.org/10.1117/1.2912053

Abstract

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.

©(2008) Society of Photo-Optical Instrumentation Engineers (SPIE)

Citation Download Citation

Ariawan Suwendi and Jan P. Allebach "Nearest-neighbor and bilinear resampling factor estimation to detect blockiness or blurriness of an image," Journal of Electronic Imaging 17(2), 023005 (1 April 2008). https://doi.org/10.1117/1.2912053

Published: 1 April 2008

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