Two-Pass Robust Component Analysis for Cloud Removal in Satellite Image Sequence

2018 ◽  
Vol 15 (7) ◽  
pp. 1090-1094 ◽  
Author(s):  
Fei Wen ◽  
Yongjun Zhang ◽  
Zhi Gao ◽  
Xiao Ling
Keyword(s):  
Satellite Image ◽  
Image Sequence ◽  
Component Analysis ◽  
Cloud Removal

scholarly journals CLOUD REMOVAL FROM SENTINEL-2 IMAGE TIME SERIES THROUGH SPARSE RECONSTRUCTION FROM RANDOM SAMPLES

2016 ◽  
Vol XLI-B3 ◽  
pp. 469-473
Author(s):  
D. Cerra ◽  
J. Bieniarz ◽  
R. Müller ◽  
P. Reinartz
Keyword(s):  
Time Series ◽  
Satellite Image ◽  
Reconstruction Error ◽  
Sparse Reconstruction ◽  
Shadow Mask ◽  
Spectral Evolution ◽  
Random Samples ◽  
Restoration Algorithm ◽  
Cloud Removal ◽  
Sentinel 2

In this paper we propose a cloud removal algorithm for scenes within a Sentinel-2 satellite image time series based on synthetisation of the affected areas via sparse reconstruction. For this purpose, a clouds and clouds shadow mask must be given. With respect to previous works, the process has an increased automation degree. Several dictionaries, on the basis of which the data are reconstructed, are selected randomly from cloud-free areas around the cloud, and for each pixel the dictionary yielding the smallest reconstruction error in non-corrupted images is chosen for the restoration. The values below a cloudy area are therefore estimated by observing the spectral evolution in time of the non-corrupted pixels around it. The proposed restoration algorithm is fast and efficient, requires minimal supervision and yield results with low overall radiometric and spectral distortions.

scholarly journals Detection and Tracking Method of Maritime Moving Targets Based on Geosynchronous Orbit Satellite Optical Images

Electronics ◽  
2020 ◽  
Vol 9 (7) ◽  
pp. 1092
Author(s):  
Fengqi Xiao ◽  
Fei Yuan ◽  
En Cheng
Keyword(s):  
Satellite Image ◽  
Image Sequence ◽  
Geosynchronous Orbit ◽  
Optical Remote Sensing ◽  
Large Area ◽  
Tracking Method ◽  
Detection And Tracking ◽  
Orbit Satellite ◽  
Optical Images ◽  
Long Time

The GF-4 geosynchronous orbit satellite can observe a large area for a long time, but the unique characteristics of its optical remote sensing image restrict the detection of maritime targets. This paper proposes a maritime target detection and tracking method for the GF-4 satellite image sequence based on the differences in information between frames in the image sequence. First, a preprocessing method is proposed for the unique characteristics of the image. Then, the ViBe (Visual Background Extractor) algorithm is used to extract the targets in the image sequence. After detection, the DCF-CSR (discriminative correlation filters with channel and spatial reliability) is used as a tracker to track and correlate the detected target to complete the task of predicting and monitoring the targets’ movements. Finally, through the comparative analysis of experiments with several classic methods, the feasibility and effectiveness of this method are verified.

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