Integrated Photogrammetric and Photoclinometric Processing of Multiple HRSC Images for Pixelwise 3-D Mapping on Mars

Images from the high-resolution stereo camera (HRSC) is an important data source for retrieving 3-D information of the Martian surface. Photogrammetry has been widely applied to HRSC images to generate digital elevation models (DEMs). However, in circumstances of insufficient textures or severe atmospheric influences on Mars, photogrammetry may fail to generate DEMs of favorable quality. Besides, photogrammetry is not able to recover pixelwise geometrical information. Meanwhile, photoclinometry is a promising method to retrieve pixelwise 3-D information from image intensities. Few works in the past have explored the appropriate use of photoclinometry for HRSC data. This article presents an innovative approach of integrating photogrammetry and photoclinometry for pixelwise 3-D mapping of the Martian surface using multiple HRSC images. First, an effective photogrammetric strategy is developed to process multiple HRSC images. For images influenced by haze or aerosol problems, an automatic object-based matching algorithm is formulated to compensate for obvious flaws on the disparity map. Second, multiview photoclinometry considering atmospheric effect is developed to refine the photogrammetric DEM to pixel resolution. Qualitative and quantitative validations are conducted using two representative sets of HRSC images and compared with the reference data. The results show that the generated DEMs have good geometric consistency with the reference data, but offer subtle topographic details conforming to the original images. The proposed method provides a promising solution to exploit the HRSC images for 3-D mapping of the Martian surface with better resolution and coverage, which is of significance for future Mars exploration missions and scientific research.

Automated summary

This article proposes an innovative approach to integrate photogrammetry and photoclinometry for pixelwise 3-D mapping of the Martian surface using multiple HRSC images, improving the quality and resolution of terrain data. Through qualitative and quantitative validations, the results show that the generated DEMs have good geometric consistency with reference data, but offer subtle topographic details that align with the original images.