Volume IV-4/W4
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-4/W4, 209-213, 2017
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.
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-4/W4, 209-213, 2017
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.

  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 S. Eken et al.
  • Kocaeli University, Dept. of Computer Engineering, 41380, İzmit Kocaeli, Turkey

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.