@inproceedings{0c0da376fe0d44adae30c02f94fe3465,
title = "A Robust Unwrapping Method for Local Noise Phase",
abstract = "Phase unwrapping algorithm is difficult to apply in INSAR image for the local high-density noise phase attributed to significant blocky noise. To achieve its application in such case, the pixels of noise phase are first detected, and are set to 0 with the automatic mask technique. For the phase that has a blocky noise region, the iteration algorithm of phase filling based on Least-Squares is developed in this study by calculating the unwrapping coefficient k to rebuild the true phase. The algorithm is promoted by MPIPU's ability to fill in the missing phase; it can also significantly suppress the error transfer attributed to iteration filling in the non-mask phase. Some experiments are performed on simulated data. As revealed from the results, the proposed method exhibits robust performance of phase unwrapping on local noise phase.",
keywords = "Optical Measurement, Phase Unwrapping, Remote Sensing Monitoring",
author = "Quan Wu and Qida Yu and Jing Yang and Xianchun Zhou",
note = "Publisher Copyright: {\textcopyright} 2022 SPIE.; 2022 International Conference on Signal Processing and Communication Security, ICSPCS 2022 ; Conference date: 22-07-2022 Through 24-07-2022",
year = "2022",
doi = "10.1117/12.2655186",
language = "English",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Min Xiao and Lisu Yu",
booktitle = "International Conference on Signal Processing and Communication Security, ICSPCS 2022",
}