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Distance-based edge detection on synthetic aperture radar imagery

journal contribution
posted on 28.05.2021, 20:21 by ADC Nascimento, KF Silva, Alejandro Frery
Synthetic aperture radar is an efficient remote sensing tool by producing high spacial resolution images. But, synthetic aperture radar data suffer speckle noise effect that difficult their processing (for example, making boundary detection). We propose and assess edge detectors for synthetic aperture radar imagery based on stochastic distances between models.These edge detectors stem from generalized divergences with good asymptotic properties. Results reveal that divergence-based detectors can outperform the likelihood-based counterpart.

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Preferred citation

Nascimento, A. D. C., Silva, K. F. & Frery, A. C. (2021). Distance-based edge detection on synthetic aperture radar imagery. Chilean Journal of Statistics, 12(1), 71-82.

Journal title

Chilean Journal of Statistics

Volume

12

Issue

1

Publication date

01/04/2021

Pagination

71-82

Publication status

Published

ISSN

0718-7912

eISSN

0718-7920

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