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Inflated Rayleigh Distribution for SAR Imagery Modeling

Palm, Bruna (author)
Blekinge Tekniska Högskola,Institutionen för matematik och naturvetenskap
Javadi, Saleh, 1986- (author)
Blekinge Tekniska Högskola,Institutionen för matematik och naturvetenskap
Bayer, Fabio M. (author)
Universidade Federal de Santa Maria, BRA
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Vu, Viet Thuy, 1977- (author)
Blekinge Tekniska Högskola,Institutionen för matematik och naturvetenskap
Pettersson, Mats, 1966- (author)
Blekinge Tekniska Högskola,Institutionen för matematik och naturvetenskap
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 (creator_code:org_t)
Institute of Electrical and Electronics Engineers (IEEE), 2022
2022
English.
In: International Geoscience and Remote Sensing Symposium (IGARSS 2022). - : Institute of Electrical and Electronics Engineers (IEEE). - 9781665427920 ; , s. 44-47
  • Conference paper (peer-reviewed)
Abstract Subject headings
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  • Synthetic aperture radars (SAR) data plays an important role in remote sensing applications. It is common knowledge that SAR image amplitude pixels can be approximately modeled by the Rayleigh distribution. However, this model is contin-uous and does not accommodate points with non-zero prob-ability, such as a null pixel amplitude value. Thus, in this paper, we propose an inflated Rayleigh distribution for SAR image modeling that is based on a mixed continuous-discrete distribution and can be used to fit signals with observed values on [0, infty). The maximum likelihood approach is considered to estimate the parameters of the proposed distribution. An empirical experiment with a SAR image is also presented and discussed. © 2022 IEEE.

Subject headings

TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik -- Signalbehandling (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering -- Signal Processing (hsv//eng)

Keyword

Maximum likelihood estimation
Null amplitude value
Rayleigh distribution
SAR images

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