Karakus, Oktay  ORCID: https://orcid.org/0000-0001-8009-9319, Kuruoglu, Ercan E., Achim, Alin M. and Altinkaya, Mustafa A.
2022.
Cauchy-Rician model for backscattering in urban SAR images.
IEEE Geoscience and Remote Sensing Letters
19
, 4504905.
10.1109/LGRS.2022.3146370
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Abstract
This paper presents a new statistical model for urban scene SAR images by combining the Cauchy distribution, which is heavy-tailed, with the Rician back-scattering. The literature spans various well-known models most of which are derived under the assumption that the scene consists of multitudes of random reflectors. This idea specifically fails for urban scenes since they accommodate a heterogeneous collection of strong scatterers such as buildings, cars, wall corners. Moreover, when it comes to analysing their statistical behaviour, due to these strong reflectors, urban scenes include a high number of high amplitude samples, which implies that urban scenes are mostly heavy-tailed. The proposed Cauchy-Rician model contributes to the literature by leveraging non-zero location (Rician) heavy-tailed (Cauchy) signal components. In the experimental analysis, the Cauchy-Rician model is investigated in comparison to state-of-the-art statistical models that include G0, generalized gamma, and the lognormal distribution. The numerical analysis demonstrates the superior performance and flexibility of the proposed distribution for modelling urban scenes.
| Item Type: | Article |
|---|---|
| Date Type: | Publication |
| Status: | Published |
| Schools: | Schools > Computer Science & Informatics |
| Subjects: | Q Science > Q Science (General) T Technology > TA Engineering (General). Civil engineering (General) |
| Publisher: | Institute of Electrical and Electronics Engineers |
| ISSN: | 1545-598X |
| Funders: | Engineering and Physical Sciences Research Council (Grant Number: EP/R009260/1) |
| Date of First Compliant Deposit: | 25 February 2022 |
| Date of Acceptance: | 26 January 2022 |
| Last Modified: | 03 Dec 2024 06:45 |
| URI: | https://orca.cardiff.ac.uk/id/eprint/147747 |
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