Name
Abstract | ||
|---|---|---|
The performance of a super-resolution (SR) reconstruction method on real-world data is not easy to measure, especially as a ground-truth (GT) is often not available. In this paper, a quantitative performance measure is used, based on triangle orientation discrimination (TOD). The TOD measure, simulating a real-observer task, is capable of determining the performance of a specific SR reconstruction method under varying conditions of the input data. It is shown that the performance of an SR reconstruction method on real-world data can be predicted accurately by measuring its performance on simulated data. This prediction of the performance on real-world data enables the optimization of the complete chain of a vision system; from camera setup and SR reconstruction up to image detection/recognition/identification. Furthermore, different SR reconstruction methods are compared to show that the TOD method is a useful tool to select a specific SR reconstruction method according to the imaging conditions (camera's fill-factor, optical point-spread-function (PSF), signal-to-noise ratio (SNR)). |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1155/2007/43953 | EURASIP J. Adv. Sig. Proc. |
Keywords | Field | DocType |
signal to noise ratio,ground truth,super resolution,vision system,electronics,point spread function | Computer vision,Machine vision,Image sensor,Detection theory,Image detection,Computer science,Signal-to-noise ratio,Artificial intelligence,Observer (quantum physics),Point spread function,Superresolution | Journal |
Volume | Issue | ISSN |
2007 | 1 | 1687-6180 |
Citations | PageRank | References |
4 | 0.53 | 11 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Adam W. M. van Eekeren | 1 | 32 | 2.53 |
| Klamer Schutte | 2 | 173 | 18.26 |
| Olivier R. Oudegeest | 3 | 4 | 0.53 |
| Lucas J. van Vliet | 4 | 842 | 113.16 |