Paper
3 October 2022 Multiple image super-resolution from the BGU SWIR CubeSat satellite
Author Affiliations +
Abstract
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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Itai Dror, Divya Mishra, Ron Shmueli, Dan Blumberg, Shimrit Maman, Daniel Choukroun, and Ofer Hadar "Multiple image super-resolution from the BGU SWIR CubeSat satellite", Proc. SPIE 12226, Applications of Digital Image Processing XLV, 122260I (3 October 2022); https://doi.org/10.1117/12.2633778
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KEYWORDS
Satellites

Image quality

Super resolution

Satellite imaging

Image fusion

Lawrencium

Short wave infrared radiation

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