Description: In a recent NASA ROSES solicitation, NASA has expressed strong interest in improving surface characterization of Mars using orbital imagers. Thermal Emission Imaging System (THEMIS) and Thermal Emission Spectrometer (TES) are orbital multispectral imagers of Mars. THEMIS has 10 spectral bands in the 6-13 micrometers region and a spatial resolution of 100 m. TES has 143 spectral bands in the 5-50 micrometers range, but with low spatial resolution of 3x3 km. Although both have been used to map out the surface composition of Mars, there are some limitations. First, THEMIS has low spectral resolution that may not provide accurate surface characterization. Second, TES has low spatial resolution that cannot provide fine spatial details of surface characteristics. Roughly speaking, each TES pixel contains about 900 THEMIS pixels. It is therefore very challenging to fuse the two data sets. We propose a novel and accurate framework that can deal with the above challenge. The framework is based on the latest development in image registration, image fusion, anomaly detection, pixel classification using hyperspectral images, and concentration estimation. First, a two-step image registration algorithm is proposed to align the THEMIS and TES bands. Subpixel accuracy can be achieved. Second, a novel image fusion algorithm is proposed to fuse THEMIS and TES bands to generate an image cube with 143 bands of 100-m resolution images. Our algorithm has been proven to be better than state-of-the-art fusion algorithms. Third, we propose a novel anomaly detection algorithm for detecting interesting regions in the fused image cube. This algorithm is known as cluster kernel Reed Xiaoli (CKRX) and has high performance in anomaly detection. Fourth, a sparsity based approach is proposed to perform accurate rock classification. Finally, a deep learning based algorithm is proposed to estimate the chemical composition of the rocks for better surface characterization.

Benefits: Accurate Mars surface characterization will be important for Mars exploration. It should be noted that, for Earth observations, there are imagers that are similar to the above instruments for Mars. For example, the Worldview-3 imager collects high resolution visible and short-wave infrared (SWIR) images at sub-meter resolution whereas the NASA's Moderate Resolution Imaging Spectroradiometer (MODIS), NOAA's Advanced Very High Resolution Radiometer (AVHRR), etc. are collecting low resolution (hundreds of meters) multispectral images. For some future hyperspectral imagers like the NASA HyspIRI with hundreds of bands as shown in website: http://hyspiri.jpl.nasa.gov/science, the spatial resolution is only about 30 meters. It will be good to fuse the high resolution Worldview images with MODIS, AVHRR, and HyspIRI images to yield high resolution in both spatial and spectral domains. Consequently, many applications, including urban monitoring, vegetation monitoring, fire and flood damage assessment, etc., will benefit from the high spatial and high spectral resolution images.

Our proposed surface characterization system can be used for military surveillance and reconnaissance and civilian applications such as border patrol, coastal monitoring, vegetation monitoring, urban development monitoring, etc. The combined market can be over 5 million dollars over the next decade. The market size is based on an estimated of users of 5,000 and a unit price of $1,000 per software.