Mr. Daniel Choukroun Profile

Daniel Choukroun

at Ben-Gurion Univ. of the Negev

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Proceedings Article | 3 October 2022 Paper

Multiple image super-resolution from the BGU SWIR CubeSat satellite

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

Proceedings Volume 12226, 122260I (2022) https://doi.org/10.1117/12.2633778

KEYWORDS: Satellites, Image quality, Super resolution, Satellite imaging, Image fusion, Short wave infrared radiation, Lawrencium, Image registration, Earth observing sensors, Remote sensing

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The BGU CubeSat satellite is from a class of low-cost, compact satellites. Its dimensions are 10×10×30 cm. It is equipped with a low resolution 256×320 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 nonreference 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.

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