Many image quality and image difference metrics have been proposed over the last decades. An
important factor when evaluating
the image quality or image difference is the viewing distance. In this talk we present an
image difference metric based on the simulation of detail visibility and total variation. The
simulation of detail visibility takes into account the viewing conditions and the viewing
distance, and calculation of the image difference is done by total variation.
Further, we also present the results of an extensive evaluation of 60 state-of-the-art image
quality metrics, including well-known metrics, such as SSIM, multiscale SSIM, VIF, MSE, S-DEE, CID,
MAD, S-CIELAB, SHAME, VSNR, and PSNR. Evaluation is performed on the on the Colourlab Image
Database: Image Quality (CID:IQ), a database consisting of 690 images where the subjective data has
been collected at two different viewing distances. The performance of the image quality metrics is
assessed in terms of correlation to subjective data.
At least, we will also touch upon aspects that influence subjective quality assessment;
including high level visual masking and short term memory.
Marius Pedersen is professor at the Norwegian University of Science and Technology. His work is
centered on image quality assessment; he has more than 60 publications in this field. He received
his PhD in color imaging (2011) from the University of Oslo. He is currently the head of the
computer science group in GjÃ¸vik in the department of computer science, as well as the head of the
Norwegian Colour and Visual Computing Laboratory, both at NTNU.
University of Konstanz, Powerwall Room C202
Unfortunately, the talk will not be transmitted to Stuttgart and TÃ¼bingen.