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17 February 2006 Nearest-neighbor and bilinear resampling factor estimation to detect blockiness or blurriness of an image
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Proceedings Volume 6076, Digital Publishing; 60760C (2006) https://doi.org/10.1117/12.647924
Event: Electronic Imaging 2006, 2006, San Jose, California, United States
Abstract
In digital publishing, a low-resolution image is highly undesirable. Inexperienced users often try to include lowresolution 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. In this paper, 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 post-processing algorithms is also evaluated.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ariawan Suwendi and Jan P. Allebach "Nearest-neighbor and bilinear resampling factor estimation to detect blockiness or blurriness of an image", Proc. SPIE 6076, Digital Publishing, 60760C (17 February 2006); https://doi.org/10.1117/12.647924
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