Regarding the quality of disparity estimation from distorted light fields

Abstract

Recent developments in the field of plenoptic imaging have directly coincided with standardisation efforts. Such efforts are in no small part reliant on quality evaluations. For traditional imaging modalities, such as static images and videos, subjective evaluations have played a very important part. The goal of most objective quality evaluations has been the correlation performance with subjective results. However, plenoptic modalities enable applications that rely more on the objective rather than subjective quality. As such, it is necessary to examine the performance of currently used objective quality metrics. The paper provides a study on the predictive abilities of objective quality metrics on the quality of light field disparity map estimation. The study measures the influence of distortions on light field disparity estimations; furthermore, the study examines how well can objective quality metrics predict the quality of the resulting disparity maps. None of the tested metrics showed satisfactory prediction performance. Thus, two metric fusion algorithms were also examined to see if either can further improve prediction accuracy. The metric fusion algorithms showed that the prediction can be significantly improved. A novel objective quality metric that would correlate well with both subjective and objective results could thus be introduced.