Non-local means SAR despeckling based on scattering
- 1 July 2015
- conference paper
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE) in 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
- p. 3172-3174
- https://doi.org/10.1109/igarss.2015.7326491
Abstract
Speckle reduction in Synthetic Aperture Radar (SAR) images is an essential pre-processing step for a correct analysis and interpretation of SAR data. This justifies the huge effort in the image processing community to develop more and more accurate despeckling techniques in order to reduce speckle effects and then improve readability of SAR imagery also for non SAR expert users. Up to now, nonlocal means approaches provide the most promising and effective despeckling performances. In this paper we develop a new non-local means despeckling technique based on electromagnetic scattering mechanisms. The proposed method, based on a physically meaningful similarity criterion for distance evaluation, is theoretically assessed, tested on a simulated SAR image, and compared to the state of the art.Keywords
This publication has 7 references indexed in Scilit:
- Optical-Driven Nonlocal SAR DespecklingIEEE Geoscience and Remote Sensing Letters, 2014
- On shape from shading and SAR images: An overview and a new perspectivePublished by Institute of Electrical and Electronics Engineers (IEEE) ,2014
- Benchmarking Framework for SAR DespecklingIEEE Transactions on Geoscience and Remote Sensing, 2013
- A Nonlocal SAR Image Denoising Algorithm Based on LLMMSE Wavelet ShrinkageIEEE Transactions on Geoscience and Remote Sensing, 2011
- Iterative Weighted Maximum Likelihood Denoising With Probabilistic Patch-Based WeightsIEEE Transactions on Image Processing, 2009
- A Review of Image Denoising Algorithms, with a New OneMultiscale Modeling & Simulation, 2005
- SARAS: a synthetic aperture radar (SAR) raw signal simulatorIEEE Transactions on Geoscience and Remote Sensing, 1992