计算机科学
斑点图案
卷积神经网络
绝对相位
人工智能
干涉合成孔径雷达
连贯性(哲学赌博策略)
散斑噪声
相(物质)
接头(建筑物)
相位展开
滤波器(信号处理)
噪音(视频)
干涉测量
计算机视觉
相位噪声
模式识别(心理学)
算法
合成孔径雷达
图像(数学)
光学
电子工程
数学
工程类
物理
建筑工程
有机化学
化学
统计
作者
Giampaolo Ferraioli,Vito Pascazio,Gilda Schirinzi,Sergio Vitale,Mengdao Xing,Hanwen Yu,Lifan Zhou
标识
DOI:10.1109/igarss47720.2021.9554726
摘要
In this paper the effectiveness of a CNN based interferometric phase unwrapping algorithm combined with phase noise filtering is analysed. In particular, the considered processing chain relies on a pre-processing step with the nonlocal filter InSAR-BM3D followed by a deep CNN solution for restoring the absolute phase. The analyses is conducted on simulated data with different coherence values and aims at comparing the performance of the unwrapping with and without the pre-processing step. This paper is the first step towards a unique deep learning solution for jointly unwrapping and restoring the absolute phase.
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