Low-Complexity Multispectral Images Compression Algorithm Based Distributed Compressive Sensing

Author(s):  
Longxu Jin ◽  
Jin Li ◽  
Min Zhang ◽  
Yinan Wu
2009 ◽  
Author(s):  
Dror Baron ◽  
Marco F. Duarte ◽  
Michael B. Wakin ◽  
Shriram Sarvotham ◽  
Richard G. Baraniuk

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 1994
Author(s):  
Qian Ma ◽  
Wenting Han ◽  
Shenjin Huang ◽  
Shide Dong ◽  
Guang Li ◽  
...  

This study explores the classification potential of a multispectral classification model for farmland with planting structures of different complexity. Unmanned aerial vehicle (UAV) remote sensing technology is used to obtain multispectral images of three study areas with low-, medium-, and high-complexity planting structures, containing three, five, and eight types of crops, respectively. The feature subsets of three study areas are selected by recursive feature elimination (RFE). Object-oriented random forest (OB-RF) and object-oriented support vector machine (OB-SVM) classification models are established for the three study areas. After training the models with the feature subsets, the classification results are evaluated using a confusion matrix. The OB-RF and OB-SVM models’ classification accuracies are 97.09% and 99.13%, respectively, for the low-complexity planting structure. The equivalent values are 92.61% and 99.08% for the medium-complexity planting structure and 88.99% and 97.21% for the high-complexity planting structure. For farmland with fragmentary plots and a high-complexity planting structure, as the planting structure complexity changed from low to high, both models’ overall accuracy levels decreased. The overall accuracy of the OB-RF model decreased by 8.1%, and that of the OB-SVM model only decreased by 1.92%. OB-SVM achieves an overall classification accuracy of 97.21%, and a single-crop extraction accuracy of at least 85.65%. Therefore, UAV multispectral remote sensing can be used for classification applications in highly complex planting structures.


2014 ◽  
Vol 11 (3) ◽  
pp. 20130947-20130947 ◽  
Author(s):  
Dongeun Lee ◽  
Jaesik Choi ◽  
Heonshik Shin

2015 ◽  
Author(s):  
Rui Lei ◽  
Wei Shen ◽  
Zhi-jiang Zhang ◽  
Ying Zhou

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