21 December 2000 SAR interferometric phase denoising: a new approach based on wavelet transform
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Abstract
This paper describes the use of the wavelet transform for interferometric noise filtering in synthetic aperture radar (SAR). The interferometric phase noise is characterised by an additive noise model. This noise is also non-station ary, therefore some filtering schemes use a windowing process to take into account this behaviour, but the performance of the noise removal process will be highly related with the dimensions of the window. A new approach to solve this problem is presented. This new algorithm is based on the wavelet transform, allowing to process the phase without using the windowing process. The interferometric phase is not processed directly, but in the complex plane using a complex number containing the same phase information. This approach allows to maintain the phase jumps that are very important in the unwrapping process. A new noise model is proposed both in the original and in the wavelet domain. Using this noise model, the noise removal algorithm is presented. Results, using both synthetic and real phase images, are shown. Parameters that characterize the phase signal, as the number of residues and statistical parameters are also presented. The results show that there is a clear improvement in the phase signal.
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Carlos Lopez, Francesc Xavier Fabregas, "SAR interferometric phase denoising: a new approach based on wavelet transform", Proc. SPIE 4173, SAR Image Analysis, Modeling, and Techniques III, (21 December 2000); doi: 10.1117/12.410656; https://doi.org/10.1117/12.410656
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