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
2016-01-01

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.
2016
9781450342971
9781450342971
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].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11590/308022
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