English

DIFET: Distributed Feature Extraction Tool For High Spatial Resolution Remote Sensing Images

Distributed, Parallel, and Cluster Computing 2018-08-28 v1

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.

Keywords

Cite

@article{arxiv.1808.08521,
  title  = {DIFET: Distributed Feature Extraction Tool For High Spatial Resolution Remote Sensing Images},
  author = {Suleyman Eken and Eray Aydin and Ahmet Sayar},
  journal= {arXiv preprint arXiv:1808.08521},
  year   = {2018}
}

Comments

Presented at 4th International GeoAdvances Workshop

R2 v1 2026-06-23T03:43:58.765Z