An  increase  in  research  activity  around  plenoptic  content  can  be  seen  in  recent  years.   As  the  communities around the different modalities grow, so does the demand for publicly available annotated datasets of suitable content.  The datasets can be used for a multitude of purposes, such as to design novel compression algorithms,subjective evaluation methodologies or objective quality metrics. In this work, a new publicly available annotated light field image dataset is presented.  The dataset consists of scenes corrupted by state-of-the-art image and video compression algorithms (JPEG, JPEG 2000, BPG, VP9, AV1, AVC, HEVC), noise, and geometric distortion.  For the subjective evaluation of the included scenes, a modified version of the Double Stimulus Impairment Scale (DSIS) methodology was adopted.  The views of each scene were organized in a pseudo-sequence and played to the observers as animations.  The resulting objective and subjective scores, together with additional data, are included in the dataset.  The dataset can be used to evaluate the performance of currently used visual quality metrics as well as for the design of new ones.

Raw scores and additional information about participants available for download via: