@inproceedings{85a699bf5c174b1db0403d8cff2f9be0,
title = "Double MRF for water classification in SAR images by joint detection and reflectivity estimation",
abstract = "Classification of SAR images is a challenging task as the radiometric properties of a class may not be constant throughout the image. The assumption made in most classification algorithms that a class can be modeled by constant parameters is then not valid. In this paper, we propose a classification algorithm based on two Markov random fields that accounts for local and global variations of the parameters inside the image and produces a regularized classification. This algorithm is applied on airborne TropiSAR and simulated SWOT HR data. Both quantitative and visual results are provided, demonstrating the effectiveness of the proposed method.",
keywords = "Classification, MRF, SAR, SWOT",
author = "Sylvain Lobry and Loic Denis and Florence Tupin and Roger Fjortoft",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 37th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2017 ; Conference date: 23-07-2017 Through 28-07-2017",
year = "2017",
month = dec,
day = "1",
doi = "10.1109/IGARSS.2017.8127445",
language = "English",
series = "International Geoscience and Remote Sensing Symposium (IGARSS)",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "2283--2286",
booktitle = "2017 IEEE International Geoscience and Remote Sensing Symposium",
}