Noise reduction methods for terrain phase estimation of InSAR images


Lee, Sui Ping and Chan, Yee Kit and Lim, Tien Sze and Koo, Voon Chet (2016) Noise reduction methods for terrain phase estimation of InSAR images. In: 2016 IEEE 12th International Colloquium on Signal Processing & Its Applications (CSPA). IEEE, pp. 167-172. ISBN 978-1-4673-8780-4

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Despite decades of scientists' effort, absolute phase determination of interferometry synthetic aperture radar (InSAR) image still remains unsolved. InSAR measurement derived from phase data is not only ambiguous by its modulo-2pi mathematical-ill pose, but also further corrupted by noise. Therefore, we suggest an adaptive least mean square (LMS) algorithm based on steepest descent method for noise reduction purpose. Besides, a scheme which incorporates such filter into a Itoh two-dimensional phase-unwrapping is proposed. The phase estimation procedures are implemented to reconstruct a simulated interferogram of terrain structure. For the quantitative assessment, we employ different types of quality metrics to measure the estimated outcome of InSAR terrain image which includes root mean square error (RMSE) and signal-to-noise ratio (SNR). The estimated outcomes are also reconstructed into three dimensional plotting for visual assessment. By refering to the similar scheme, other noise reduction filters include wieners filter and median filter are implemented for performance comparison. The simulated results show that the proposed method is able to filter noise without corrupted the useful phase information and achieves lowest error energy among other filters. Thus, it is a valuable technique for InSAR terrain phase estimation.

Item Type: Book Section
Uncontrolled Keywords: Wiener filters, Signal to noise ratio, Phase estimation, Filtering algorithms, Finite impulse response filters, Mathematical model
Subjects: T Technology > TD Environmental technology. Sanitary engineering > TD878-894 Special types of environment Including soil pollution, air pollution, noise pollution
Divisions: Faculty of Engineering and Technology (FET)
Depositing User: Ms Suzilawati Abu Samah
Date Deposited: 07 Feb 2018 12:20
Last Modified: 07 Feb 2018 12:20


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