  This paper presents a full-reference image quality estimator based on color,
structure, and visual system characteristics denoted as CSV. In contrast to the
majority of existing methods, we quantify perceptual color degradations rather
than absolute pixel-wise changes. We use the CIEDE2000 color difference
formulation to quantify low-level color degradations and the Earth Mover's
Distance between color name descriptors to measure significant color
degradations. In addition to the perceptual color difference, CSV also contains
structural and perceptual differences. Structural feature maps are obtained by
mean subtraction and divisive normalization, and perceptual feature maps are
obtained from contrast sensitivity formulations of retinal ganglion cells. The
proposed quality estimator CSV is tested on the LIVE, the Multiply Distorted
LIVE, and the TID 2013 databases, and it is always among the top two performing
quality estimators in terms of at least ranking, monotonic behavior or
linearity.
