Name
Abstract | ||
|---|---|---|
Thermal cameras can not be calibrated as easily as RGB cameras, since their noise characteristics change over time; thus scene-based non-uniformity correction SBNUC has been developed. We present a method to boost the convergence of these algorithms by removing the readout noise form the image before it is processed. The readout noise can be estimated by capturing a series of pictures with varying exposure times, fitting a line for each pixel and thereby estimating the bias of the pixel. When this is subtracted from the image a noticeable portion of the noise is compensated. We compare the results of two common SBNUC algorithms with and without this compensation. The mean average error improves by several orders of magnitude, which allows faster convergence with smaller step sizes. The readout noise compensation RNC can be used to improve the performance of any SBNUC approach. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1007/978-3-319-29451-3_26 | PSIVT |
Field | DocType | Volume |
Noise compensation,Computer science,Electronic engineering,Distributed computing | Conference | 9431 |
ISSN | Citations | PageRank |
0302-9743 | 0 | 0.34 |
References | Authors | |
2 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Martin Bürker | 1 | 0 | 0.34 |
| Hendrik P. A. Lensch | 2 | 1471 | 96.59 |