The Ames Stereo Pipeline: Automated 3D Surface Reconstruction from Orbital Imagery

Introduction: The Mars Orbital Laser Altimeter (MOLA) has significantly advanced the study of the Martian surface by providing geologists with a highly accurate elevation map of the entire planet [1]. However, its limited resolution (463m/pixel at the equator) and localized interpolation artifacts have rendered it insufficient for detailed studies of specific sites; e.g. geologic stratification and deposition analysis, or in the case of mission planning, landing site selection. The most common technique for obtaining higherresolution digital terrain models (DTMs) is to employ stereogrammetric techniques, however the substantial number of man-hours and resources required for this aproach has meant that relatively few of these data products have reached the scientific community. To address this problem, the Intelligent Robotics Group (IRG) at NASA Ames Research Center has developed an automated stereo processing software system, the Ames Stereo Pipeline (ASP), that is capable of generating high quality DTMs from orbital imagery using a fully automated process [2]. Approach: The image processing pipeline for the ASP can be broken down as follows. First, images are pre-processed by applying the “Sign of the Laplacian of the Gaussian” (SLOG) filter introduced by Nishihara [3]. This filter is a composition of Laplacian and Gaussian filters followed by the application of a threshold step, which results in increased robustness to lighting variation in the stereo pair. For dense stereo correlation, the ASP implements a fast area based sum of absolute difference (SOAD) correlation algorithm. The resulting disparity map encodes the offsets between matching pixels in the stereo pair. Several versions of this correlator are available including a multi-scale implementation which first computes a low resolution stereo disparity map that is then refined at successively higher levels of detail until the native resolution of the source images has been reached. Further performance is gained by adaptively partitioning the stereo images into tiles to minimize the disparity search range for any given tile. A final 3D point cloud is calculated from the disparity map by computing the closest point of intersection of two rays emanating from the cameras through the matched pixels. The ASP includes several camera models that describe the geometry of various imagers including an adaptation of the linear push-broom model [4] of line-scan imagers; a geometry that is found in many modern orbiting camera platforms. Several final data products can be generated from the 3D point cloud including 3D triangle meshes (e.g. VRML models) and ortho-rectified, map projected DTMs and camera imagery. Results: Typical processing times are on the order of minutes to tens of minutes depending on the resolution of the images. A level of quality assessment and control that is useful for many applications can be achieved with minimal human involvement. The ASP is being used in existing collaborations with Malin Space Science Systems (MSSS) and the US Geological Survey (USGS) to generate DTMs from the Narrow Angle Mars Orbital Camera (MOC-NA) (Figures 1 and 2), the MRO Context Camera (CTX), the High Resolution Stereo Camera (HRSC), and the Apollo Panoramic & Metric Cameras (Figure 3). Current and Future Activities: As work on the Ames Stereo Pipeline continues, our focus will be on integration, validation, and scalability. In particular, we have begun work in the following areas: Integration with widely adopted cartographic software: The USGS Integrated Software for Imagers and Spectrometers (ISIS) package is widely used in the planetary science community for processing raw spacecraft imagery into high level data products of scientific interest such as map projected and mosaicked imagery [5,6]. We are enabling the ASP to read ISIS image files and to utilize ISIS camera models, thereby allowing scientists to prepare data for stereo processing using a familiar tool-chain and peer reviewed camera photometric and geometric calibration.