Name
Abstract | ||
|---|---|---|
To achieve auto exposure in digital cameras, image brightness is widely used because of its direct relationship with exposure value. To use image entropy as an alternative statistic to image brightness, it is required to establish how image entropy changes as exposure value is varied. This paper presents a mathematical proof along with experimental verification results to show that image entropy reaches a maximum value as exposure value is varied by changing shutter speed or aperture size. (C) 2011 SPIE and IS&T. [DOI: 10.1117/1.3534855] |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1117/1.3534855 | JOURNAL OF ELECTRONIC IMAGING |
Field | DocType | Volume |
Aperture,Computer vision,Statistic,Pattern recognition,Exposure,Computer science,Shutter speed,Mathematical proof,Artificial intelligence,Exposure value,Brightness | Journal | 20 |
Issue | ISSN | Citations |
1 | 1017-9909 | 3 |
PageRank | References | Authors |
0.83 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| M. Rahman | 1 | 52 | 4.64 |
| Nasser D. Kehtarnavaz | 2 | 534 | 66.02 |
| Qolamreza R. Razlighi | 3 | 35 | 5.51 |