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Post classification smoothing in sub-decimeter resolution images with semi-supervised label propagation


Vargas-Munoz, John E; Tuia, Devis; dos Santos, Jefersson A; Falcao, Alexandre X (2017). Post classification smoothing in sub-decimeter resolution images with semi-supervised label propagation. In: 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Fort Worth, 23 July 2017 - 28 July 2017, 3688-3691.

Abstract

In this paper, we propose a post classification smoothing method aimed at improving the accuracy and visual appearance of sub-decimeter image classification results. Starting from the class confidence maps of a supervised classifier, we find a set of high confidence markers and propagate labels on an extended region adjacency graph. We apply the proposed method on a challenging 5cm resolution dataset over Potsdam, Germany. The proposed algorithm outperforms state-of-the-art post classification smoothing algorithms both when the classifier is trained specifically on the image and when it is trained and tested in different set of images.

Abstract

In this paper, we propose a post classification smoothing method aimed at improving the accuracy and visual appearance of sub-decimeter image classification results. Starting from the class confidence maps of a supervised classifier, we find a set of high confidence markers and propagate labels on an extended region adjacency graph. We apply the proposed method on a challenging 5cm resolution dataset over Potsdam, Germany. The proposed algorithm outperforms state-of-the-art post classification smoothing algorithms both when the classifier is trained specifically on the image and when it is trained and tested in different set of images.

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Additional indexing

Item Type:Conference or Workshop Item (Paper), not_refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Geography
Dewey Decimal Classification:910 Geography & travel
Language:English
Event End Date:28 July 2017
Deposited On:23 Mar 2018 15:09
Last Modified:20 Sep 2018 04:31
Publisher:IEEE
ISBN:978-1-5090-4951-6
OA Status:Closed
Publisher DOI:https://doi.org/10.1109/IGARSS.2017.8127799

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