Name
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.
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Year | DOI | Venue |
|---|---|---|
2016 | 10.1145/2910017.2910623 | MMSys'16: Multimedia Systems Conference 2016
Klagenfurt
Austria
May, 2016 |
Keywords | Field | DocType |
Light Field imaging, Plenoptics, Quality of Experience, Content Attributes, SMART Light Field Dataset | Computer vision,Colorfulness,Image texture,Computer science,Light-field camera,Image processing,Image quality,Light field,Artificial intelligence,Digital image processing,Multimedia,Depth of field | Conference |
ISBN | Citations | PageRank |
978-1-4503-4297-1 | 3 | 0.43 |
References | Authors | |
14 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Pradip Paudyal | 1 | 54 | 4.97 |
| Roger Olsson | 2 | 57 | 5.64 |
| Mårten Sjöström | 3 | 174 | 19.69 |
| federica battisti | 4 | 18 | 1.72 |
| Marco Carli | 5 | 252 | 28.85 |