Abstract
Higher resolution imaging data of planetary surfaces is considered desirable by the international community of planetary scientists interested in improving understanding of surface formation processes. However, given various physical constraints from the imaging instruments through to limited bandwidth of transmission one needs to trade-off spatial resolution against bandwidth. Even given optical communications, future imaging systems are unlikely to be able to resolve features smaller than 25cm on most planetary bodies, such as Mars. In this paper, we propose a novel super-resolution restoration technique, called Gotcha-PDE-TV (GPT), taking advantage of the non-redundant sub-pixel information contained in multiple raw orbital images in order to restore higher resolution imagery. We demonstrate optimality of this technique in planetary image super-resolution restoration with example processing of 8 repeat-pass 25cm HiRISE images covering the MER-A Spirit rover traverse in Gusev crater to resolve a 5cm resolution of the area. We assess the “true” resolution of the 5cm super-resolution restored images using contemporaneous rover Navcam imagery on the surface and an inter-comparison of landmarks in the two sets of imagery.
Highlights
Higher resolution imaging data of planetary surfaces is considered desirable by the international community of planetary scientists interested in improving understanding of surface formation processes
We propose a further optimized Total Variation (TV) algorithm, called Gotcha-Partial Differential Equation (PDE)-TV, based on an unique adaptive least-squares correlation (ALSC) matcher called P-Gotcha described in Shin and Muller (2012) which has been successfully applied to topographic mapping and co-registration of multi-view imagery from HRSC, CTX and HiRISE in Kim and Muller (2009)
We developed a Mutual Shape Adapted Scaled Invariant Feature Transform (SIFT) (MSA-SIFT) algorithm that uses forward and backward ALSC to iteratively search for a correct TP by adjusting the shape of the correlation matching window as shown in Eq (10), where Xi is an ALSC searching window starting from the origin of the initial TPs
Summary
Higher resolution imaging data of planetary surfaces is considered desirable by the international community of planetary scientists interested in improving understanding of surface formation processes. We propose a novel super-resolution restoration technique, called Gotcha-PDE-TV (GPT), taking advantage of the non-redundant sub-pixel information contained in multiple raw orbital images in order to restore higher resolution imagery. With various physical constraints from the imaging instruments themselves, not the least of which is “launch mass” and volume, one needs to be able to trade-off spatial resolution and bandwidth for any remote sensing system This suggests that even with optical communications, future imaging systems are unlikely to be able to resolve features smaller than 25 cm given constraints on telescope mass and size. This is the experience for civilian Earth Observing satellites where the highest spatial resolution is % 30 cm from WorldView-3. Each view is subjected to different atmospheric blurring and scattering but as long as the atmospheric transparency is sufficiently high, Gotcha-PDE-TV SRR can be applied
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