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Detection and Segmentation of Different Structures from Satellite Images

A large number of satellite images has been collected over the years with the help of orbiter missions to Mars such as Mars Reconnaissance Orbiter. By detecting certain structures such as impact craters in these images, information about past geological processes can be gathered as well as it provides a means to measure the relative ages of other geologic formations. The detection of dunes from these images can assist in providing clues about the transformation of climate in the Martian atmosphere. Other analogous Martian features such as transverse Aeolian ridges and volcanic rootless cones can also be detected utilizing these high-resolution images. Ascertaining these different structures and features will also be used to plan future surface and lander missions to Mars which needs safe route planning and other geological analysis. Manually detecting and segmenting structures is not practical as a consequence a fully autonomous system needs to be designed which will be able to detect all the previously mentioned structures. Convolutional Neural Networks are some of the methods that can be used for processing these images and extract the necessary features.