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Novel Object-Based Filter for Improving Land-Cover Classification of Aerial Imagery with Very High Spatial Resolution

Novel Object-Based Filter for Improving Land-Cover Classification of Aerial Imagery with Very High Spatial Resolution


Titill: Novel Object-Based Filter for Improving Land-Cover Classification of Aerial Imagery with Very High Spatial Resolution
Höfundur: Lv, Zhiyong
Shi, Wenzhong
Benediktsson, Jon Atli   orcid.org/0000-0003-0621-9647
Xiaojuan, Ning
Útgáfa: 2016-12-15
Tungumál: Enska
Umfang: 1023
Háskóli/Stofnun: Háskóli Íslands
University of Iceland
Svið: Verkfræði- og náttúruvísindasvið (HÍ)
School of Engineering and Natural Sciences (UI)
Deild: Rafmagns- og tölvuverkfræðideild (HÍ)
Faculty of Electrical and Computer Engineering (UI)
Birtist í: Remote Sensing;8(12)
ISSN: 2072-4292
DOI: 10.3390/rs8121023
Efnisorð: Image filter; Spatial resolution; Aerial image; Multiscale segmentation; Land cover classification; Litrófsgreining; Myndvinnsla; Loftmyndir; Landmælingar
URI: https://hdl.handle.net/20.500.11815/385

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Tilvitnun:

Lv, Z.; Shi, W.; Benediktsson, J.A.; Ning, X. Novel Object-Based Filter for Improving Land-Cover Classification of Aerial Imagery with Very High Spatial Resolution. Remote Sens. 2016, 8, 1023. doi:10.3390/rs8121023

Útdráttur:

Land cover classification using very high spatial resolution (VHSR) imaging plays a very important role in remote sensing applications. However, image noise usually reduces the classification accuracy of VHSR images. Image spatial filters have been recently adopted to improve VHSR image land cover classification. In this study, a new object-based image filter using topology and feature constraints is proposed, where an object is considered as a central object and has irregular shapes and various numbers of neighbors depending on the nature of the surroundings. First, multi-scale segmentation is used to generate a homogeneous image object and extract the corresponding vectors. Then, topology and feature constraints are proposed to select the adjacent objects, which present similar materials to the central object. Third, the feature of the central object is smoothed by the average of the selected objects’ feature. This proposed approach is validated on three VHSR images, ranging from a fixed-wing aerial image to UAV images. The performance of the proposed approach is compared to a standard object-based approach (OO), object correlative index (OCI) spatial feature based method, a recursive filter (RF), and a rolling guided filter (RGF), and has shown a 6%–18% improvement in overall accuracy.

Leyfi:

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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