The availability of an image dataset is useful for design, testing, and benchmarking Light Field image processing algorithms. As first step, the image content selection criteria have been defined based on selected image quality key-attributes, i.e. spatial information, colorfulness, texture key features, depth of field, etc. Next, image scenes have been selected and captured by using the Lytro Illum Light Field camera. Performed analysis shows that the considered set of images is sufficient for addressing a wide range of attributes relevant to assess Light Field image quality. 16 LF images are included in the SMART LF dataset. The images are from both indoor and outdoor category, and cover general image content related features (colorfulness, spatial information, and texture) but also LF specific aspects such as reflection, transparency and depth of field variation.
References and Citation
Use of the datasets in published work should be acknowledged by a full citation to the authors’ papers at the MMSys conference: Proceedings of ACM MMSys’16, Klagenfurt am Wörthersee, Austria, May 10-13, 2016. [link]
In addition, please cite the following baseline for the no-reference quality metric: