Acta Optica Sinica, Volume. 39, Issue 5, 0528006(2019)
Persistent Scatterer Detection Method Based on Empirical Mode Decomposition
Fig. 1. EMD decomposition results of one-dimensional signal. (a) Original signal with noise; (b) imf1 component; (c) imf2 component; (d) imf3 component; (e) imf4 component; (f) residual trend component
Fig. 2. Schematics of multidirectional decomposition of image. (a) Horizontal direction; (b) left diagonal direction; (c) vertical direction; (d) right diagonal direction
Fig. 3. Scattergram of PSC points after initial selection
Fig. 4. Phase comparison of differential interferograms before and after filtering. (a) Original interferogram with noise; (b) interferogram denoised by EMD; (c) interferogram denoised by improved EMD
Fig. 5. Phase of PSC points before and after filtering. (a) Before filtering; (b) after filtering
Fig. 6. Distribution histogram of PSC points
Fig. 7. Probability density function p(γg) of γg
Fig. 8. Final scatter gram of PS points in study area
Fig. 9. Scattergrams of PS points detected by different methods. (a) Amplitude deviation index threshold method; (b) coherence coefficient threshold method; (c) phase deviation index threshold method; (d) EMD method
Fig. 10. Scattergrams of PS points detected by different methods. (a) Amplitude deviation index threshold method; (b) coherence coefficient threshold method; (c) phase deviation index threshold method; (d) EMD method; (e) proposed method
|
|
|
Get Citation
Copy Citation Text
Changjun Huang, Jiyuan Hu, Yafu Yang. Persistent Scatterer Detection Method Based on Empirical Mode Decomposition[J]. Acta Optica Sinica, 2019, 39(5): 0528006
Category: Remote Sensing and Sensors
Received: Nov. 1, 2018
Accepted: Feb. 19, 2019
Published Online: May. 10, 2019
The Author Email: