@article{998dad682b004b9eac3cbb4669db4f0f,
title = "HPT: A high spatial resolution multispectral sensor for microsatellite remote sensing",
abstract = "Although nano/microsatellites have great potential as remote sensing platforms, the spatial and spectral resolutions of an optical payload instrument are limited. In this study, a high spatial resolution multispectral sensor, the High-Precision Telescope (HPT), was developed for the RISING-2 microsatellite. The HPT has four image sensors: three in the visible region of the spectrum used for the composition of true color images, and a fourth in the near-infrared region, which employs liquid crystal tunable filter (LCTF) technology for wavelength scanning. Band-to-band image registration methods have also been developed for the HPT and implemented in the image processing procedure. The processed images were compared with other satellite images, and proven to be useful in various remote sensing applications. Thus, LCTF technology can be considered an innovative tool that is suitable for future multi/hyperspectral remote sensing by nano/microsatellites.",
keywords = "Earth observation, Image analysis, Microsatellite, Multispectral sensor, Tunable filter",
author = "Junichi Kurihara and Yukihiro Takahashi and Yuji Sakamoto and Toshinori Kuwahara and Kazuya Yoshida",
note = "Funding Information: Acknowledgments: This research was supported by the microsatellite research and development program of the Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan. This research was also supported by the Japan Society for the Promotion of Science (JSPS) Core-to-Core Program, B. Asia-Africa Science Platforms. The scale-invariant feature transform algorithm, available from the OpenCV library, was used for feature matching. Landsat images were downloaded from the United States Geological Survey website Author Contributions: J.K. and Y.T. conceived and designed the experiments; Y.S., T.K., and K.Y. performed the experiments and contributed materials; J.K. analyzed the data and wrote the paper. Publisher Copyright: {\textcopyright} 2018 by the authors. Licensee MDPI, Basel, Switzerland.",
year = "2018",
month = feb,
day = "18",
doi = "10.3390/s18020619",
language = "English",
volume = "18",
journal = "Sensors",
issn = "1424-3210",
publisher = "Multidisciplinary Digital Publishing Institute (MDPI)",
number = "2",
}