Paper
24 September 2007 New quality metrics for digital image resizing
Hongseok Kim, Soundar Kumara
Author Affiliations +
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.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Hongseok Kim and Soundar Kumara "New quality metrics for digital image resizing", Proc. SPIE 6696, Applications of Digital Image Processing XXX, 669608 (24 September 2007); https://doi.org/10.1117/12.735400
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Cited by 1 scholarly publication.
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KEYWORDS
Image quality

Digital imaging

Medical imaging

Image processing

Digital image processing

Human vision and color perception

Image restoration

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