Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Bivariate Gamma Distribution for Wavelength-Resolution SAR Change Detection
Blekinge Institute of Technology, Faculty of Engineering, Department of Mathematics and Natural Sciences.
Universidade Federal de Santa Maria, BRA.
Blekinge Institute of Technology, Faculty of Engineering, Department of Mathematics and Natural Sciences.ORCID iD: 0000-0002-6643-312x
Saab Surveillance, SWE.
Show others and affiliations
2019 (English)In: IEEE Transactions on Geoscience and Remote Sensing, ISSN 0196-2892, E-ISSN 1558-0644, Vol. 57, no 1, p. 473-481Article in journal (Refereed) Published
Abstract [en]

A gamma probability density function (pdf) is shown to be an alternative to model the distribution of the magnitudes of high-resolution, i.e., wavelength-resolution, synthetic aperture radar (SAR) images. As investigated in this paper, it is more appropriate and more realistic statistical in comparison with, e.g., Rayleigh. A bivariate gamma pdf is considered for developing a statistical hypothesis test for wavelength-resolution incoherent SAR change detection. The practical issues in implementation of statistical hypothesis test, such as assumptions on target magnitudes, estimations for scale and shape parameters, and implementation of modified Bessel function, are addressed. This paper also proposes a simple processing scheme for incoherent change detection to validate the proposed statistical hypothesis test. The proposal was experimented with 24 CARABAS data sets. With an average detection probability of 96%, the false alarm rate is only 0.47 per square kilometer. IEEE

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc. , 2019. Vol. 57, no 1, p. 473-481
Keywords [en]
Bivariate gamma, CARABAS, change detection, synthetic aperture radar (SAR)., Probability density function, Probability distributions, Radar imaging, Statistical tests, Tracking radar, Bivariate, Bivariate gamma distribution, Probability density function (pdf), Scale and shape parameters, Statistical hypothesis test, Synthetic aperture radar (SAR) images, Synthetic aperture radar
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:bth-16936DOI: 10.1109/TGRS.2018.2856926ISI: 000455089000036Scopus ID: 2-s2.0-85051396922OAI: oai:DiVA.org:bth-16936DiVA, id: diva2:1241567
Available from: 2018-08-24 Created: 2018-08-24 Last updated: 2019-01-28Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records BETA

Vu, Viet ThuyPettersson, Mats

Search in DiVA

By author/editor
Vu, Viet ThuyPettersson, Mats
By organisation
Department of Mathematics and Natural Sciences
In the same journal
IEEE Transactions on Geoscience and Remote Sensing
Other Electrical Engineering, Electronic Engineering, Information Engineering

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 109 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf