Advantages of the Boresight Effect in Hyperspectral Data Analysis
Abstract
:1. Introduction
2. Boresight Effect in a Multisensor System
N | Mean | Std. | Variance | Skewness | ||
---|---|---|---|---|---|---|
Statistic | Statistic | Std. Error | Statistic | Statistic | Statistic | Std. Error |
255 255 | 2,706.325 | 569.6115 | 9,095.966 | 8.3E + 07 | 4.132 | 0.153 |
3. Boresight Applications: Results and Discussion
3.1. Enhancing the Shadow Effect
Class ID | Boresight value (band ratio) | Shadow fraction (ground truth) |
---|---|---|
#1 (maroon) | 4–3.4 | 80–100% |
#2 (magenta) | 3.4–2.5 | 50–80% |
#3 (cyan) | 2.5–2.1 | 20–50% |
#4 (yellow) | 2.1–1.9 | 10–20% |
3.2. Stereo 3-D Map
3.3. Unmixing and Anomaly Detection
4. Discussion
5. Conclusions
References and Notes
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Brook, A.; Ben-Dor, E. Advantages of the Boresight Effect in Hyperspectral Data Analysis. Remote Sens. 2011, 3, 484-502. https://doi.org/10.3390/rs3030484
Brook A, Ben-Dor E. Advantages of the Boresight Effect in Hyperspectral Data Analysis. Remote Sensing. 2011; 3(3):484-502. https://doi.org/10.3390/rs3030484
Chicago/Turabian StyleBrook, Anna, and Eyal Ben-Dor. 2011. "Advantages of the Boresight Effect in Hyperspectral Data Analysis" Remote Sensing 3, no. 3: 484-502. https://doi.org/10.3390/rs3030484