Name
Abstract | ||
|---|---|---|
Cloud removal is significantly needed for enhancing the further utilization of Landsat imagery, since such optical remote sensing satellite images are inevitably contaminated by clouds. Clouds dynamically affect the signal transmission due to their different shapes, heights, and distribution. Generally, pixel replacement is the only and common method used to remove thick opaque clouds, and radiometric correction techniques has been widely adopted to remove the thin clouds. However, no methods can remove both thick and thin clouds at the same time. In this paper, a new method is proposed based on fitting "trajectory" of cloudy pixels with the help of IHOT spatially charactering clouds for pixel correction, which considers signal transmission including not only the additive reflectance from the clouds but also the energy attenuation when solar radiation passes through them. The experimental results show that the proposed approach performs effective removal for thick and thin clouds, and possesses the highest accuracy with the reference image, which can restore land cover information accurately. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/IGARSS.2016.7729111 | 2016 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS) |
Keywords | Field | DocType |
iterated HOT (IHOT), cloud-thickness, trajectory, cloud removal, Landsat imagery | Transmission (telecommunications),Computer vision,Satellite,Computer science,Remote sensing,Opacity,Artificial intelligence,Pixel,Attenuation,Image restoration,Cloud fraction,Trajectory | Conference |
ISSN | Citations | PageRank |
2153-6996 | 0 | 0.34 |
References | Authors | |
5 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shuli Chen | 1 | 8 | 1.22 |
| Xuehong Chen | 2 | 47 | 11.12 |
| Jin Chen | 3 | 259 | 31.87 |
| Xin Cao | 4 | 15 | 5.20 |