Single Image Super-Resolution Restoration of TGO CaSSIS Colour Images: Demonstration with Perseverance Rover Landing Site and Mars Science Targets

Abstract

The ExoMars Trace Gas Orbiter (TGO)’s Colour and Stereo Surface Imaging System (CaSSIS) provides multi-spectral optical imagery at 4–5 m/pixel spatial resolution. Improving the spatial resolution of CaSSIS images would allow greater amounts of scientific information to be extracted. In this work, we propose a novel Multi-scale Adaptive weighted Residual Super-resolution Generative Adversarial Network (MARSGAN) for single-image super-resolution restoration of TGO CaSSIS images, and demonstrate how this provides an effective resolution enhancement factor of about 3 times. We demonstrate with qualitative and quantitative assessments of CaSSIS SRR results over the Mars2020 Perseverance rover’s landing site. We also show examples of similar SRR performance over 8 science test sites mainly selected for being covered by HiRISE at higher resolution for comparison, which include many features unique to the Martian surface. Application of MARSGAN will allow high resolution colour imagery from CaSSIS to be obtained over extensive areas of Mars beyond what has been possible to obtain to date from HiRISE.

Keywords

• super-resolution restoration
• SRR
• Generative Adversarial Network
• GAN
• TGO
• CaSSIS