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Two-Step Multitemporal Nonlocal Means for Synthetic Aperture Radar Images

Abstract : This paper presents a denoising approach for multitemporal synthetic aperture radar (SAR) images based on the concept of nonlocal means (NLM). It exploits the information redundancy existing in multitemporal images by a two-step strategy. The first step realizes a nonlocal weighted estimation driven by the redundancy in time, whereas the second step makes use of the nonlocal estimation in space. Using patch similarity missregistration estimation, we also adapted this approach to the case of unregistered SAR images. The experiments illustrate the efficiency of the proposed method to denoise multitemporal images while preserving new information.
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Submitted on : Monday, March 15, 2021 - 12:13:38 PM
Last modification on : Tuesday, October 19, 2021 - 11:15:17 AM
Long-term archiving on: : Wednesday, June 16, 2021 - 6:43:38 PM

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Charles-Alban Deledalle, Florence Tupin, Xin Su. Two-Step Multitemporal Nonlocal Means for Synthetic Aperture Radar Images. IEEE Transactions on Geoscience and Remote Sensing, Institute of Electrical and Electronics Engineers, 2014, 52, pp.6181 - 6196. ⟨10.1109/tgrs.2013.2295431⟩. ⟨hal-03169399⟩

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