ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume IV-4/W4
Articles | Volume IV-4/W4
https://doi.org/10.5194/isprs-annals-IV-4-W4-209-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/isprs-annals-IV-4-W4-209-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume IV-4/W4
13 Nov 2017
 | 13 Nov 2017

DIFET: DISTRIBUTED FEATURE EXTRACTION TOOL FOR HIGH SPATIAL RESOLUTION REMOTE SENSING IMAGES

S. Eken, E. Aydın, and A. Sayar

Keywords: Distributed Feature Extraction, Apache Hadoop, HIPI, Big Data, Remote Sensing

Abstract. In this paper, we propose distributed feature extraction tool from high spatial resolution remote sensing images. Tool is based on Apache Hadoop framework and Hadoop Image Processing Interface. Two corner detection (Harris and Shi-Tomasi) algorithms and five feature descriptors (SIFT, SURF, FAST, BRIEF, and ORB) are considered. Robustness of the tool in the task of feature extraction from LandSat-8 imageries are evaluated in terms of horizontal scalability.

How to cite. Eken, S., Aydın, E., and Sayar, A.: DIFET: DISTRIBUTED FEATURE EXTRACTION TOOL FOR HIGH SPATIAL RESOLUTION REMOTE SENSING IMAGES, ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-4/W4, 209–213, https://doi.org/10.5194/isprs-annals-IV-4-W4-209-2017, 2017.