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Proceedings Paper

New quality metrics for digital image resizing
Author(s): Hongseok Kim; Soundar Kumara
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Paper Abstract

Digital image rescaling by interpolation has been intensively researched over past decades, and still getting constant attention from many applications such as medical diagnosis, super-resolution, image blow-up, nano-manufacturing, etc. However, there are no consented metrics to objectively assess and compare the quality of resized images. Some existing measures such as peak-signal-to-noise ratio (PSNR) or mean-squared error (MSE), widely used in image restoration area, do not always coincide with the opinions from viewers. Enlarged digital images generally suffer from two major artifacts: blurring, zigzagging, and those undesirable effects especially around edges significantly degrade the overall perceptual image quality. We propose two new image quality metrics to measure the degree of the two major defects, and compare several existing interpolation methods using the proposed metrics. We also evaluate the validity of image quality metrics by comparing rank correlations.

Paper Details

Date Published: 24 September 2007
PDF: 8 pages
Proc. SPIE 6696, Applications of Digital Image Processing XXX, 669608 (24 September 2007); doi: 10.1117/12.735400
Show Author Affiliations
Hongseok Kim, Pennsylvania State Univ. (United States)
Soundar Kumara, Pennsylvania State Univ. (United States)

Published in SPIE Proceedings Vol. 6696:
Applications of Digital Image Processing XXX
Andrew G. Tescher, Editor(s)

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