Textural noise correction for sentinel-1 TOPSAR cross-polarization channel images

Jeong Won Park, Joong Sun Won, Anton A. Korosov, Mohamed Babiker, Nuno Miranda

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

The thermal noise-induced distortions in a Sentinel-1 terrain observation with progressive scans synthetic aperture radar image cannot be corrected by the noise equivalent sigma nought (NESZ) subtraction only. Since the thermal noise is scaled during synthetic aperture radar processing, it resides not only as an additive noise in each pixel but also as a multiplicative noise in the interpixel contrast. In this paper, we investigate the noise characteristics and propose an efficient method for the multiplicative textural noise correction. The core ideas are to find the optimal coefficient of the noise-induced standard deviation (SD) and model the noise contribution to the local SD as a function of the NESZ and the signal-to-noise ratio. Denoising is accomplished by a subwindow-wise adaptive rescaling of the pixel values. The improvements in the first- and second-order statistical textural features demonstrate the effectiveness of the proposed method.

Original languageEnglish
Article number8630667
Pages (from-to)4040-4049
Number of pages10
JournalIEEE Transactions on Geoscience and Remote Sensing
Volume57
Issue number6
DOIs
Publication statusPublished - 2019 Jun

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All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering
  • Earth and Planetary Sciences(all)

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