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.