TY - GEN
T1 - A Modified Kalman-Filter Method for Scalloping Suppression with Gaofen-3 SAR Images
AU - Li, Yihan
AU - Yang, Wei
AU - Chen, Jie
AU - Li, Chunsheng
AU - Zou, Fei
AU - Guo, Yu
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/7
Y1 - 2019/7
N2 - ScanSAR images are widely used in both military and civil fields with the capability of wide swath. However, the scalloping effect seriously affects the quality of scanSAR images, especially in the complex scenes, e.g. the sea-land junction scene. This paper presents a modified Kalman-filter method for scalloping suppression. First, the scanSAR image model is built, considering the scalloping effect and noise. Then, Kalman filter is adopted for suppressing the scalloping effect. Moreover, pre-processing method, on the basis of image statistical characteristics, is implemented to accommodate complex scene. Specifically, the pre-processing, involving image segmentation and brightness filling, divides the image into sub-images with different brightness and provides linear-Gaussian condition for Kalman filter through brightness filling. Finally, the method is verified by GaoFen-3(GF-3) SAR images, with the discussion and conclusion.
AB - ScanSAR images are widely used in both military and civil fields with the capability of wide swath. However, the scalloping effect seriously affects the quality of scanSAR images, especially in the complex scenes, e.g. the sea-land junction scene. This paper presents a modified Kalman-filter method for scalloping suppression. First, the scanSAR image model is built, considering the scalloping effect and noise. Then, Kalman filter is adopted for suppressing the scalloping effect. Moreover, pre-processing method, on the basis of image statistical characteristics, is implemented to accommodate complex scene. Specifically, the pre-processing, involving image segmentation and brightness filling, divides the image into sub-images with different brightness and provides linear-Gaussian condition for Kalman filter through brightness filling. Finally, the method is verified by GaoFen-3(GF-3) SAR images, with the discussion and conclusion.
KW - Coastal Zones
KW - GaoFen-3
KW - Kalman Filter
KW - Scalloping
KW - ScanSAR
UR - https://www.scopus.com/pages/publications/85077698601
U2 - 10.1109/IGARSS.2019.8899340
DO - 10.1109/IGARSS.2019.8899340
M3 - 会议稿件
AN - SCOPUS:85077698601
T3 - International Geoscience and Remote Sensing Symposium (IGARSS)
SP - 2953
EP - 2956
BT - 2019 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 39th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019
Y2 - 28 July 2019 through 2 August 2019
ER -