Advanced Statistical Techniques in SAR Image Processing and Analysis

A GRSL special stream – 2018
· Prof. Luis Gómez – Universidad las Palmas de Gran Canaria, Spain (Lead Guest Associate Editor)
· Prof. Avik Bhattacharya – Indian Institute of Technology, Mumbai, India (Guest Associate Editor)
· Prof. Juliana Gambini – Instituto Tecnológico de Buenos Aires, Argentina (Guest Associate Editor)
· Prof. Anthony Doulgeris – Norges Arktiske Universitet, Norway (Guest Associate Editor)

Techniques derived from Information Theory, Information Geometry and Robust Inference
have become an essential tool for image processing and analysis. In particular, these techniques
can be used to tackle diverse and challenging problems in mono-polarized (amplitude and
intensity) and full-polarimetric SAR (PolSAR) images (viz. feature extraction, parameter
estimation, image classification, image segmentation, edge and change detection, noise
reduction, polarization rotation correction).

The elegant new techniques and the results that stem from the use of advanced statistical
methods for SAR data are few and unfortunately scattered in the literature of Pattern
Recognition, Mathematical Statistics and Signal Processing. This fragmentation does not
promote a unified view of this emerging field of research and, thus, many find it difficult to
embrace a comprehensive body of theory and results. This Special Stream aims at filling such
gap with a selection of contributions that share a common viewpoint.

The objective of the Special Issue, open to all researchers, is to select outstanding contributions
on recent advances in the field of advanced statistical techniques applied to synthetic aperture
radar, bringing together participants from the research, academic and industrial communities.

Contributions on topics of primary interest are expected. These include:

  • Statistical techniques in SAR/PolSAR analysis,
  • Statistical techniques for SAR/PolSAR image processing,
  • Target decompositions theorems for PolSAR data,
  • SAR/PolSAR image classification and regression,
  • SAR/PolSAR image denoising,
  • Edge detection for SAR/PolSAR data,
  • Techniques for evaluating and improving despeckling filters,
  • Target recognition,
  • Techniques for change detection.

Submission Guidelines
This special issue solicits original work that is not under consideration for publication in other
venues. Authors must refer to the IEEE Geoscience and Remote Sensing Letters authors’ guide
at for information on content and formatting of submissions.
The direct link to the Manuscript Central for the submission of papers is In the Manuscript type drop-down menu box, the
author must choose Special Section on “Advanced Statistical Techniques in SAR Image
Processing and Analysis”.

Submission open: 1 April 2018
Submission close: 30 September 2018

We are providing to the interested participants a fully-polarimetric UAVSAR L-band dataset to assess the proposed approaches, enhancing the reproducibility of their contributions. Authors will be free to use it or not, in the way they find it most suitable.

L_band UAVSAR:

For Speckle Filtering: