A Review of Image Quality Assessment with application to Computational Photography
Résumé
Image quality assessment has been of major importance for several domains of the industry of image as for
instance restoration or communication and coding. New application fieds are opening today with the increase
of embedded power in the camera and the emergence of computational photography: automatic tunning, image
selection, image fusion, image data-base building, etc.
We review the literature of image quality evaluation. We pay attention to the very dfferent undelying
hypotheses and results of the existing methods to approach the problem. We explain why they dffer and for
which applications they may be beneficial. We also underline their limits, especialy for a possible use in the novel
domain of computational photography. Being developed to address dfferent objectives, they propose answers
on dfferent aspects, which make them sometimes complementary. However, they all remain limited in their
capability to challenge the human expert, the said or unsaid ultimate goal.
We consider the methods which are based on retrieving the parameters of a signal, mostly in spectral analysis;
then we explore the more global methods to qualify the image quality in terms of noticeable defects or degradation
as popular in the compression domain; in a third field the image acquisition process is considered as a channel
between the source and the receiver, allowing to use the tools of the information theory and to qualify the system
in terms of entropy and information capacity.
However, these dfferent approaches hardly attack the most dffcult part of the task which is tomeasure
the quality of the photography in terms of aesthetic properties. To help in addressing this problem, in between
Phylosophy, Biology and Psychology, we propose a brief review of the litterature which addresses the problematic
of qualifying Beauty, present the attempts to adapt these concepts to visual patterns and initiate a re
exion on
what could be done in the field of photography.