Preprint Article Version 1 NOT YET PEER-REVIEWED

Removing Striping Noise from Cloudy Level 2 Sea Surface Temperature and Ocean Color Datasets

  1. Institut Mines Télécom - Télécom Bretagne, UMR 6285 LabSTICC CS 83818 - 29238 Brest Cedex 3 - France
  2. Laboratoire d’Océanographie Physique et Spatial (LOPS), IFREMER, Centre Bretagne - ZI de la Pointe du Diable - CS 10070 - 29280 Plouzané
Version 1 : Received: 3 October 2016 / Approved: 3 October 2016 / Online: 3 October 2016 (20:39:17 CEST)

How to cite: Boussidi, B.; Fablet, R.; Chapron, B. Removing Striping Noise from Cloudy Level 2 Sea Surface Temperature and Ocean Color Datasets. Preprints 2016, 2016100002 (doi: 10.20944/preprints201610.0002.v1). Boussidi, B.; Fablet, R.; Chapron, B. Removing Striping Noise from Cloudy Level 2 Sea Surface Temperature and Ocean Color Datasets. Preprints 2016, 2016100002 (doi: 10.20944/preprints201610.0002.v1).

Abstract

This paper introduces a new destriping algorithm for remote sensing data. The method is based on combined Haar Stationary Wavelet transform and Fourier filtering. State-of-the-Art methods based on the discrete wavelet transform (DWT) may not always be effective and may cause different artifacts. Our contribution is three-fold: i) we propose to use the Undecimated Wavelet transform (UWT) to avoid as much as possible shortcomings of the classical DWT; ii) we combine a spectral filtering and UWT using the simplest possible wavelet, the Haar basis, for a computational efficiency; iii) we handle 2D fields with missing data, as commonly observed in ocean remote sensing data due to atmospheric conditions (e.g., cloud contamination). The performances of the proposed filter are tested and validated on the suppression of horizontal strip artifacts in cloudy L2 Sea Surface Temperature (SST) and ocean color snapshots.

Subject Areas

Destriping; Undecimated wavelet transform; Fourier filtering; Sea Surface Temperature; Ocean color

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