New Statistical Approaches for Turning SAR/PolSAR Data into Information
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing Image Processing".
Deadline for manuscript submissions: closed (31 December 2019) | Viewed by 8196
Special Issue Editors
Interests: remote sensing; SAR/PolSAR; speckle; statistical modelling; computer vision
Special Issues, Collections and Topics in MDPI journals
Interests: statistical computing; SAR; PolSAR; speckle; information theory; information geometry
Interests: radar signal processing; SAR target detection; marine environment; SAR GMTI
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
In this last decade, research on SAR (Synthetic Aperture Radar) and PolSAR (Polarimetric SAR) systems has received increasing interest, leading to truly innovative applications. Computational capabilities have also supported such development, allowing to better process the large available data provided by the existing SAR and PolSAR satellites and airborne systems.
To transform such daily increasing amount of high-quality, modern, remote sensing data into valuable information, new methods and new strategies are required. In this sense, new statistical models for new high-resolution SAR/PolSAR systems assisting on retrieving land information (soil moisture, cover vegetation, urban areas, ocean surface parameters, target identification) are of maximum interest for both researchers and final users.
For real-time applications, the elaboration of efficient methods to extract significant information from data remains a challenge. This Special Issue focuses on novel techniques regarding the data-to-information process related to SAR/PolSAR systems and on easing their potential applications. It covers a broad and comprehensive series of subjects related to statistical modeling, information theory, machine-learning approaches, data acquisition, and data delivery to users for immediate assimilation. Topics may also include emerging statistical models for signal processing and image interpretation.
For this Special Issue, we invite submissions on, but not limited to, the following topics:
- Statistical models for SAR/PolSAR data
- Modern Classification/Segmentation Methods
- Information Theory for SAR/PolSAR applications
- Inference
- Statistical signal processing of SAR/PolSAR data
- Machine learning
- Statistical representation of SAR/PolSAR data
- Statistical insights of noise modelling
- Denoising
Dr. Luis Gómez Déniz
Prof. Alejandro C. Frery
Dr. Gui Gao
Guest Editors
Manuscript Submission Information
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Keywords
- SAR
- PolSAR
- Statistical models
- Information theory
- Data representation
- Image interpretation
- Signal processing
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