Abstract

The Thermal Emission Imaging System (THEMIS) has provided the highest spatial resolution (100 m/pixel) thermal infrared (TIR) data of the surface of Mars to date. These data have enabled the discovery of many small-scale compositional units and helped to better constrain surface processes operating at these scales. However, with higher-resolution visible (VIS) instruments revealing smaller-scale surficial differences, there exists a need to detect and map compositional variability using TIR data at scales below 100 m. Because it is unlikely there will be a higher-resolution TIR instrument sent to Mars in the near future, creative image processing techniques commonly classified under the umbrella of “super-resolution” can be employed to improve or enhance the spatial resolution of the THEMIS TIR data. These approaches typically integrate another higher-resolution dataset and can either be qualitative for visual appeal, quantitative for data accuracy, or some combination of both. The super-resolution approach presented here produces enhanced TIR images that are radiometrically accurate, but also visually appealing. For the technique to be successfully applied, multi- to hyper-spectral data from two different spectral regions are required (e.g., the THEMIS TIR and VIS datasets). The focus here is to introduce this new super-resolution methodology and demonstrate its ability using existing THEMIS IR and VIS data. The quartzofeldspathic deposit in northern Syrtis Major was selected because of the spectral variability detected using the original IR resolution data and to better constrain the relationship between the small-scale surface morphology and areal extent of the deposit as well as its formation process. Despite being associated with the central peaks of two craters, the results here show no positive correlation between the small rocky outcrops and the quartzofeldspathic unit. A gradational contact exists between the unit and basaltic sands within the intercrater eolian material. The super-resolution approach offers an alternative approach to traditional sub-pixel deconvolution identification and provides a higher-resolution IR dataset for thermophysical and spectral analysis on Mars.

Full Text
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