A HVS based Perceptual Quality Estimation Measure
for Color Images
ACEEE International Journal on Signal & Image Processing, 3 (1):
6 (January 2012)Abstract
Human eyes are the best evaluation model for
assessing the image quality as they are the ultimate receivers
in numerous image processing applications. Mean squared
error (MSE) and peak signal-to-noise ratio (PSNR) are the
two most common full-reference measures for objective
assessment of the image quality. These are well known for
their computational simplicity and applicability for
optimization purposes, but somehow fail to correlate with the
Human Visual System (HVS) characteristics. In this paper a
novel HVS based perceptual quality estimation measure for
color images is proposed. The effect of error, structural
distortion and edge distortion have been taken in account in
order to determine the perceptual quality of the image
contaminated with various types of distortions like noises,
blurring, compression, contrast stretching and rotation.
Subjective evaluation using Difference Mean Opinion Score
(DMOS), is also performed for assessment of the perceived
image quality. As depicted by the correlation values, the
proposed quality estimation measure proves to be an efficient
HVS based quality index. The comparisons in results also
show better performance than conventional PSNR and
Structural Similarity (SSIM).