Reconstruction Distortion Oriented Light Field Image Dataset for Visual Communication

As a representation of three dimensional scenes, light field has received increasing attention. In light field image processing, reconstruction method plays an important role, which can not only produce dense views to improve the spatial and angular resolution of the light field, but also effectively reduce the transmission data. However, the reconstruction methods inevitably reduce the quality of light field images, so the corresponding light field image quality assessment is necessary. In this paper, a reconstruction distortion oriented light field image dataset is firstly established, with several different reconstruction methods and the corresponding subjective evaluation scores. Secondly, the subjective scoring results of source sequences and their types of distorted versions are compared and analyzed. Finally, the dataset is evaluated with the existing objective quality assessment metrics. Experimental results show that different reconstruction methods have different preferences on the input light field resolution, and the performance of the state-of-the-art objective quality metrics can be improved.