Mastcam image enhancement using estimated point spread functions

This paper summarizes some preliminary results in enhancing the spatial resolution of the left Mastcam images of the Mars Science Laboratory (MSL) onboard the Mars rover Curiosity. There are two multispectral Mastcam imagers, having 9 bands in each. The left imager has wide field of view, but low resolution whereas the right imager is just the opposite. Our goal is to investigate whether we can use the right Mastcam images to enhance the left Mastcam images. We first estimate the point spread function (PSF) between a pair of left and right Mastcam images using a sparsity based approach. We then apply the estimated PSF to enhance the other left images. Actual Mastcam images were used in our experiments. Preliminary results indicated that the image enhancement performance is mixed. That is, we can achieve good results in some left images and poor results in others. The mixed results point to a new direction for a future study, which involves the use of deep learning based on convolutional neural network (CNN) for PSF estimation and robust deblurring.