Application of Mellin-Kind Statistics to Polarimetric <inline-formula> <tex-math notation="TeX">${\cal G}$</tex-math></inline-formula> Distribution for SAR Data
- Submitting institution
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The University of Surrey
- Unit of assessment
- 12 - Engineering
- Output identifier
- 9011804_3
- Type
- D - Journal article
- DOI
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10.1109/TGRS.2013.2273176
- Title of journal
- IEEE Transactions on Geoscience and Remote Sensing
- Article number
- -
- First page
- 3513
- Volume
- 52
- Issue
- 6
- ISSN
- 0196-2892
- Open access status
- Out of scope for open access requirements
- Month of publication
- -
- Year of publication
- 2014
- URL
-
-
- Supplementary information
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-
- Request cross-referral to
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- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
-
- Research group(s)
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-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- In literature, the G-distribution was found to be the most accurate distribution in modelling SAR data but, before this paper, its applicability was limited by a more complicated parameter estimation. Here a solution to this problem is offered by using state-of-the-art Mellin-kind statistics. The result is a new class of estimators for the G-distribution that outperform the existing ones in bias, variance, mean squared error and computational time.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
