Abstract

Four NASA missions over the last forty years with onboard instruments for high-resolution orbital imaging have achieved both global coverage (with 6m CTX, 20m THEMIS-VIS and >8m Viking Orbiter cameras) as well as imaging with very high resolution in specific regions of interest (e.g. 25cm HiRISE and ≈1.5-12m MOC-NA cameras). Overall, this set of cameras have acquired more than 400,000 high-quality images of Mars with resolution between 25cm/pixel and 100m/pixel (Sidiropoulos and Muller, 2015). On the other hand, ESA has sent the only high-resolution stereo photogrammetric camera around Mars, HRSC onboard the Mars Express spacecraft, which has been mapping the Martian surface since 2004 with a resolution of 12.5 m/pixel (Jaumann et al., 2015). Initially the raw images are combined through an elaborate photogrammetric process to get (single-strip) 3D products (i.e. digital terrain models (DTMs) and derived orthorectified images (ORIs)). However, recently the processing chain has changed, and the single-strip product release was temporarily halted to be replaced by the production and release of mosaics of Mars quadrangles. The first product of this kind is the mosaic for the East part of quadrangle MC11 (i.e. the MC11-E mosaic), a product with 12.5 metres per pixel resolution in the panchromatic image and 50 metres per pixel resolution in the corresponding DTM (Gwinner et al., 2015). <br><br> Such a product provides an excellent basemap to co-register and orthorectify all NASA high-resolution (≤100m/pixel) orbital images. The need for this co-registration to HRSC comes from their poor areo-referencing, which often leads to large deviations (reaching up to several kilometres) between the area they are supposed to image and the area they are actually imaging. After co-registration, all products are projected onto an common 3D coordinate system, which allows an examination of dynamic features of Mars through the changes that happen on its surface. In this work, we present the results of the batch coregistration of all NASA high-resolution orbiter images of MC11-E, i.e. almost 8,000 images in total. This task was conducted with an in-house pipeline which was modified in order to handle the different parameters of the mosaic in comparison to single-strip HRSC products and to process the large input data volumes within a realistic time. An outline of the processing pipeline is given, along with examples of co-registered images and statistics of the co-registration performance. We demonstrate how such a time series representation of the surface will open up new areas for exploration and understanding of the Martian surface.

Highlights

  • Viking Orbiter 1, which was launched in August 1975, was the first orbiter which had on board TV cameras that could acquire high-resolution images of the Martian surface, reaching a resolution of 8m/pixel (Soffen and Snyder, 1976)

  • After Viking Orbiter, the Martian surface was mapped by highresolution images from 4 more NASA cameras:

  • Mars Orbiter Camera – Narrow Angle (MOC-NA) (Malin et al, 2010), onboard Mars Global Surveyor (MGS) that was launched in November 1996 (Albee, 2001)

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Summary

INTRODUCTION

Viking Orbiter 1, which was launched in August 1975, was the first orbiter which had on board TV cameras that could acquire high-resolution images of the Martian surface, reaching a resolution of 8m/pixel (Soffen and Snyder, 1976). Until today no NASA mission has reached Mars having onboard a 3D mapping instrument such as a stereo photogrammetric imaging system This gap has been partially filled by Mars Orbiter Laser Altimeter (MOLA) (Zuber et al, 1992), which is a laser altimeter with footprints of resolution 170m/pixel but inter-track spacing of up to 4km at the equator. The standard way to deal with this problem is to perform a repetitive and often manual coregistration of the input images into the same coordinate system Such a process was followed for the production of the mosaic of MC11-E rectangle of Mars (Gwinner et al, 2015) from 89 input images from the HRSC camera. This mosaic used single-strip images and 3D points generated from individual strips as an input, which were subsequently passed by an elaborate processing chain, which included bundle block adjustment (Bostelmann and Heipke, 2015) and radiometric correction (McGuire et al, 2016)

CO-REGISTRATION METHOD
EXPERIMENTAL RESULTS
FUTURE WORK
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