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 fields are opening today with the increase of embedded power in the camera and the emergence of computational photography: automatic tuning, image selection, image fusion, image data-base building, etc.
We review the literature of image quality evaluation. We pay attention to the very different underlying hypotheses and results of the existing methods to approach the problem. We explain why they differ and for which applications they may be beneficial. We also underline their limits, especially for a possible use in the novel domain of computational photography. Being developed to address different objectives, they propose answers on different 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 different approaches hardly attack the most difficult part of the task which is to measure the quality of the photography in terms of aesthetic properties. To help in addressing this problem, in between Philosophy, Biology and Psychology, we propose a brief review of the literature which addresses the problematic of qualifying Beauty, present the attempts to adapt these concepts to visual patterns and initiate a reflection on what could be done in the field of photography.