Multiple Image Super-Resolution from the BGU SWIR CubeSat Satellite

Itai Dror, Divya Mishra, Ron Shmueli, Dan Blumberg, Shimrit Maman, Daniel Choukroun, Ofer Hadar

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations


The BGU CubeSat satellite is from a class of low-cost, compact satellites. Its dimensions are 10x10x30 cm. It is equipped with a low resolution 256x320 pixels short wave infrared (SWIR) camera at the 1.55-1.7mm wavelength band. Images are transmitted in bursts of tens of images at a time with few pixel shifts from the first image to the last. Each image burst is suitable for Multiple Image Super Resolution (MISR) enhancements. MISR can construct a high-resolution (HR) image from several low-resolution (LR) images yielding an image that can resolve more details that are crucial for research in remote sensing. In this research, we verify the applicability of SOTA deep learning MISR models that were developed following the publication of the PROBA-V MISR satellite dataset at the visible red and near IR. Our SWIR multiple images differ from PROBA-V by the spectral band and by the method of collecting multiple images of the exact location. Our imagery data is acquired by a burst of very close temporal images. PROBA-V revisits the satellite at a period smaller than 30 days, assuming the soil dryness is about the same. We compare the results of Single Image Super-Resolution (SISR) and MISR techniques to "off-the-shelf" products. The quality of the super-resolved images is compared by non-reference metrics suitable for remote sensing applications and by experts' visual inspection. Unlike remarkable achievements by the GAN technique that can achieve very appealing results that are not always faithful to the original ground truth, the super-resolved images should preserve the original details as much as possible for further scientific remote sensing analysis.

Original languageEnglish
Title of host publicationApplications of Digital Image Processing XLV
EditorsAndrew G. Tescher, Touradj Ebrahimi
ISBN (Electronic)9781510654365
StatePublished - 1 Jan 2022
EventApplications of Digital Image Processing XLV 2022 - San Diego, United States
Duration: 22 Aug 202224 Aug 2022

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X


ConferenceApplications of Digital Image Processing XLV 2022
Country/TerritoryUnited States
CitySan Diego


  • Cubesat
  • Deep Learning
  • Multiple Image Super Resolution
  • SWIR

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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