TR2012-029

SAR Despeckle Filtering by Sparse Coding on Affinity Nets (SCAN)


    •  Porikli, F.; Sundaresan, R.; Suwa, K., "SAR Despeckle Filtering by Sparse Coding on Affinity Nets (SCAN)", European Conference on Synthetic Aperture Radar (EUSAR), ISBN: 978-3-8007=3404-7, April 2012, pp. 796-799.
      BibTeX Download PDF
      • @inproceedings{Porikli2012apr,
      • author = {Porikli, F. and Sundaresan, R. and Suwa, K.},
      • title = {SAR Despeckle Filtering by Sparse Coding on Affinity Nets (SCAN)},
      • booktitle = {European Conference on Synthetic Aperture Radar (EUSAR)},
      • year = 2012,
      • pages = {796--799},
      • month = apr,
      • isbn = {978-3-8007=3404-7},
      • url = {http://www.merl.com/publications/TR2012-029}
      • }
  • Research Area:

    Computer Vision


This paper presents a new approach for multiplicative noise removal in SAR images based on sparse coding by dictionary learning and collaborative filtering. First, an affinity net is formed by clustering log-similar image patches where a cluster is represented as a node in the net. For each cluster, an under-complete dictionary is computed using the alternative decision method that iteratively updates the dictionary and the sparse coefficients. The nodes belonging to the same cluster are then reconstructed by a sparse combination of the corresponding dictionary atoms. The reconstructed patches are finally collaboratively aggregated to build the denoised image. Experimental results demonstrate superior despeckle filtering performance.