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ORSIm Detector: A Novel Object Detection Framework in Optical Remote Sensing Imagery Using Spatial-Frequency Channel Features

Wu, Xin and Hong, Danfeng and Tian, Jiaojiao and Chanussot, Jocelyn and Li, Wei and Tao, Ran (2019) ORSIm Detector: A Novel Object Detection Framework in Optical Remote Sensing Imagery Using Spatial-Frequency Channel Features. IEEE Transactions on Geoscience and Remote Sensing, 57 (7), pp. 5146-5158. IEEE - Institute of Electrical and Electronics Engineers. ISSN 0196-2892

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With the rapid development of spaceborne imaging techniques, object detection in optical remote sensing imagery has drawn much attention in recent decades. While many advanced works have been developed with powerful learning algorithms, the incomplete feature representation still cannot meet the demand for effectively and efficiently handling image deformations, particularly objective scaling and rotation. To this end, we propose a novel object detection framework, called optical remote sensing imagery detector (ORSIm detector), integrating diverse channel features extraction, feature learning, fast image pyramid matching, and boosting strategy. ORSIm detector adopts a novel spatial-frequency channel feature (SFCF) by jointly considering the rotation-invariant channel features constructed in frequency domain and the original spatial channel features (e.g., color channel, gradient magnitude). Subsequently, we refine SFCF using learning-based strategy in order to obtain the high-level or semantically meaningful features. In the test phase, we achieve a fast and coarsely-scaled channel computation by mathematically estimating a scaling factor in the image domain. Extensive experimental results conducted on the two different airborne datasets are performed to demonstrate the superiority and effectiveness in comparison with previous state-of-the-art methods.

Item URL in elib:https://elib.dlr.de/128209/
Document Type:Article
Title:ORSIm Detector: A Novel Object Detection Framework in Optical Remote Sensing Imagery Using Spatial-Frequency Channel Features
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Wu, Xinaixueshuqian (at) gmail.comUNSPECIFIED
Hong, DanfengDanfeng.Hong (at) dlr.deUNSPECIFIED
Tian, JiaojiaoJiaojiao.Tian (at) dlr.deUNSPECIFIED
Chanussot, Jocelyninstitute nationale polytechnique de grenobleUNSPECIFIED
Li, WeiBeijing Institute of TechnologyUNSPECIFIED
Tao, RanBeijing Institute of TechnologyUNSPECIFIED
Journal or Publication Title:IEEE Transactions on Geoscience and Remote Sensing
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In ISI Web of Science:Yes
Page Range:pp. 5146-5158
Publisher:IEEE - Institute of Electrical and Electronics Engineers
Keywords:Object detection, optical remote sensing imagery, rotation invariant (RI), spatial-frequency domains.
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - Vorhaben hochauflösende Fernerkundungsverfahren
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > EO Data Science
Remote Sensing Technology Institute > Photogrammetry and Image Analysis
Deposited By: Hong, Danfeng
Deposited On:04 Jul 2019 11:53
Last Modified:04 Jul 2019 11:53

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