In this contribution, the design of a Light Field image dataset is presented. It can be useful for design, testing, and benchmarking Light Field image processing algorithms. As first step, 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 proposed set of images is sufficient for addressing a wide range of attributes relevant for assessing Light Field image quality.
Paudyal, P., Olsson, R., Sjöström, M., Battisti, F., & Carli, M. (2016). SMART: A light field image quality dataset. In Proceedings of the 7th International Conference on Multimedia Systems, MMSys 2016 (pp.374-379). Association for Computing Machinery, Inc [10.1145/2910017.2910623].
SMART: A light field image quality dataset
PAUDYAL, PRADIP;BATTISTI, FEDERICA;CARLI, Marco
2016
Abstract
In this contribution, the design of a Light Field image dataset is presented. It can be useful for design, testing, and benchmarking Light Field image processing algorithms. As first step, 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 proposed set of images is sufficient for addressing a wide range of attributes relevant for assessing Light Field image quality.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
