An Investigation of Spectral Band Selection for Hyperspectral LiDAR Technique
Abstract
:1. Introduction
2. Instrument and Dataset Description
2.1. AOTF-HSL
2.2. Dataset Description
2.3. Feature Description
3. The Proposed Method
3.1. Redundancy Information
3.2. Method Based on Inter-Class Variance
Method 1. Pseudo Code of the Proposed Method |
Input: Set the indicating variable m=M (which is 91 or 71 in this study), initialize alternative index set as the full channels, i.e. alternative index set idx = {1, 2, 3, …., m}, and initialize the selected channels index set index = {ø}. |
% Main loop |
while the stop condition is not met |
Step 1: Calculate Vinter(idx) among the classes of all the channels, using Equation (2). |
Step 2: Find maximum and second highest values of Vinter (nj) in Vinter(idx), send the index of the channel to initial index set initial = {ni, nj}, and index = {ni, nj}. The alternative set of channel index idx = {1, 2, 3, …, ni−1, ni+1, nj−1, nj+1, …, …, m}. |
Step 3: Find maximum of Vinter (nd) in Vinter(idx), send nd to the selected index set, index = {nd, index}. |
Step 4: Remove nd form the alternative set, the new alternative set idx = {idx}−{nd}. |
Step 5: Calculate the result of multiple classification with features corresponding to initial channels. |
if the result reaches 100%, |
Output the selected set {ni, nj} |
else |
go to Step 6 |
end while |
Step 6: Calculate the result of multiple classification with features corresponding to index channels. |
if the result reach 100%, |
Output the selected set {nd, ni, nj} |
else |
go to Step 3 |
end while |
Output the optimal channels corresponding to the selected set by maximum, sequenced as index = {n1, n2, nj, …, nq}. |
Step 7: Sort values of Vinter (index), send the channel index to the optimal set in turn, index2 = {nm1, nm2, …., nmq}. |
Output: The optimal channels corresponding to the optimal set, sequenced as index2 = {nm1, nm2, …., nmq}. |
4. Results and Analysis
4.1. Classification Performance
4.2. The Selected Channels
5. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
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Characteristics | Value | ||
---|---|---|---|
AOTF Crystal | VIS | NIR | SWIR |
Wavelength Range (nm) | 400–650 | 650–1100 | 1100–2400 |
Spectral resolution (nm) | 2–7 | 2–6 | 4–16 |
Response time (μs) | 10 | ||
AOTF Diffraction Efficiency | >90% | ||
Output Efficiency | >40% | ||
Polarization | Linearly Polarized |
Dataset | Categories | Number of Samples | Number of Channels | Spectrum Coverage (nm) |
---|---|---|---|---|
Dataset 1 | coal/rock | 4 | 91 | 650–1100 |
Dataset 2 | timber | 7 | 91 | 650–1100 |
Dataset 3 | ore | 6 | 91 | 650–1100 |
Dataset 4 | plant leaf | 10 | 71 | 650–1000 |
Dataset | NB | SVM | ||
---|---|---|---|---|
Normal Method | The Proposed Method | Normal Method | The Proposed Method | |
Dataset 1 | 47 | 9 | 12 | 4 |
Dataset 2 | 37 | 10 | 6 | 3 |
Dataset 3 | 55 | 2 | 16 | 3 |
Dataset 4 | 33 | 13 | 24 | 5 |
average | 43 | 8.5 | 14.5 | 3.75 |
Dataset | NB | SVM | ||
---|---|---|---|---|
Normal Method | The Proposed Method | Normal Method | The Proposed Method | |
Dataset 1 | 30 | 6 | 7 | 3 |
Dataset 2 | 7 | 3 | 5 | 2 |
Dataset 3 | 24 | 2 | 7 | 2 |
Dataset 4 | 19 | 7 | 22 | 3 |
Average | 20 | 4.5 | 10.25 | 2.5 |
Dataset | Echo Maximum | Reflectance |
---|---|---|
Dataset 1 | {5, 12, 16, 21, 33, 46, 52, 59, 75} | {21, 5, 12, 16, 33} |
Dataset 2 | {12, 15, 22, 38, 41, 45, 49, 53, 59, 67} | {7, 11, 6} |
Dataset 3 | {3, 7} | {2, 1} |
Dataset 4 | {17, 16, 18, 19, 15, 20, 2, 14, 13, 21, 62, 67, 1} | {2, 17, 16, 3, 1, 4, 5} |
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Shao, H.; Chen, Y.; Li, W.; Jiang, C.; Wu, H.; Chen, J.; Pan, B.; Hyyppä, J. An Investigation of Spectral Band Selection for Hyperspectral LiDAR Technique. Electronics 2020, 9, 148. https://doi.org/10.3390/electronics9010148
Shao H, Chen Y, Li W, Jiang C, Wu H, Chen J, Pan B, Hyyppä J. An Investigation of Spectral Band Selection for Hyperspectral LiDAR Technique. Electronics. 2020; 9(1):148. https://doi.org/10.3390/electronics9010148
Chicago/Turabian StyleShao, Hui, Yuwei Chen, Wei Li, Changhui Jiang, Haohao Wu, Jie Chen, Banglong Pan, and Juha Hyyppä. 2020. "An Investigation of Spectral Band Selection for Hyperspectral LiDAR Technique" Electronics 9, no. 1: 148. https://doi.org/10.3390/electronics9010148
APA StyleShao, H., Chen, Y., Li, W., Jiang, C., Wu, H., Chen, J., Pan, B., & Hyyppä, J. (2020). An Investigation of Spectral Band Selection for Hyperspectral LiDAR Technique. Electronics, 9(1), 148. https://doi.org/10.3390/electronics9010148