Man Peng

A continuative variable resolution digital elevation model for ground-based photogrammetry

A new digital elevation model (DEM) is presented for accurate surface representation in photogrammetric processing of stereo ground-based imagery. This model is named the continuative variable resolution DEM (cvrDEM). In contrast to traditional grid-based DEMs that have only one fixed resolution, this new model can provide resolutions that vary depending on the range represented in the ground-based imagery. Functions for deriving radial and angular resolutions from the cvrDEM have been derived, and a corresponding storage structure for the polar coordinates has been developed. Experimental results using publically available NASA Mars Exploration Rover 2003 imagery demonstrate the effectiveness of the cvrDEM model: It can significantly reduce storage space while fully maintaining the most useful level of mapping accuracy relevant to the range from the imaging station. A terrestrial laser scanning data set was also used to validate the effectiveness of the cvrDEM. A continuative variable resolution digital elevation model (cvrDEM) is proposed.cvrDEM maintains different mapping accuracies at different ranges.cvrDEM reduces storage space compared with grid DEM.cvrDEM is particularly valuable for DEM derived from ground-based imagery.Experimental results using Mars imagery and terrestrial laser scanning data demonstrated the effectiveness of cvrDEM.

Wide baseline mapping for Mars rovers

Wide-baseline mapping technology has been applied in NASA’s Mars Exploration Rover (MER) mission to improve the accuracy of mapping of far-range terrain from Rover stereo images. As a basic research topic in photogrammetry and computer vision, it is desirable to perform a comprehensive investigation on the accuracy and automation of widebaseline mapping. This paper presents the results of a systematic accuracy analysis of wide-baseline mapping through theoretical derivation and Monte Carlo simulation. Automated bundle adjustment and 3D wide-baseline mapping techniques are developed and tested using wide-baseline images acquired by the Spirit Rover. Experimental results demonstrate the effectiveness of the proposed techniques and verify that the mapping capability of rover stereo images can be extended from tens of meters (hard-baseline) to hundreds of meters using wide-baseline mapping techniques. Introduction In an unmanned planetary rover mission, 3D mapping of the surrounding terrain is of fundamental importance for safe rover navigation and for scientific investigation of geological features. During the 2003 Mars Exploration Rover (MER) mission, Navcam (navigation camera), and Pancam (panoramic camera) rover images have been extensively used for topographic mapping of both the Spirit and Opportunity landing sites; these high-accuracy maps have greatly supported rover traverse planning and scientific investigation in mission operations (Li et al., 2005; Di et al., 2008). Both Navcam and Pancam stereo cameras are mounted on the same camera bar atop a rover mast. This bar can be rotated 360° in azimuth and 90° in elevation, enabling the acquisition of full or partial panoramas by Navcam and Pancam camera systems. Navcam is an engineering stereo camera used for navigation purposes (Maki et al., 2003) while Pancam is a high-resolution, multispectral stereo panoramic imager used for scientific investigation of the morphology, topography, and geology of the two MER landing sites (Bell et al., 2003). Pancam has a longer baseline and a longer focal length than Navcam, making it more effective in mapping medium to far objects. Due to the limited length of a hard-baseline, the expected measurement error from hard-baseline stereo images is less than 1 m within a range of 27 m for Navcam and 55 m for Pancam (Di and Li, 2007). This baseline length usually satisfies the requirements of day-to-day, short-term planning. However, for long-term planning and PHOTOGRAMMETRIC ENGINEER ING & REMOTE SENS ING J u n e 2011 609 Wide Baseline Mapping for Mars Rovers Kaichang Di and Man Peng investigations of distant geological features, a mapping capability of up to hundreds of meters is desirable, making wide-baseline mapping technology necessary. A widebaseline stereo pair is formed by two or more images taken at two separate rover positions, resulting in a “soft” baseline that is much wider than the “hard” baseline designated on the camera bar (Figure 1). During Mars Exploration Rover mission operations, wide-baseline stereo images have been used to map a number of far-range major features including Husband Hill, McCool Hill, and Von Braun at the Spirit landing site as well as Endurance and Victoria Craters at the Opportunity landing site (Li et al., 2005; Di and Li, 2007; Chen, 2008). These wide-baselines were designed empirically using the parallax equation for “normal case” stereo as a reference and the wide-baseline mapping process involved quite a few manual interactions, for example, manual selection of cross-site (wide-baseline) tie points for bundle adjustment and interactive image matching to obtain terrain details (Di and Li, 2007; Chen, 2008). Photogrammetric bundle adjustment is a key technique for achieving high-precision topographic products and has been widely used in MER mission for 3D mapping as well as rover localization (Li et al., 2004 and 2005; Di and Li, 2007; Di et al., 2008). Bundle adjustment of an image network formed by relevant Pancam and Navcam stereo images generates high-precision exterior orientation parameters of the images as well as ground positions of tie points. In particular, bundle adjustment of multi-site images ensures that the mapping products generated from bundle-adjusted images are of high accuracy and geometrically seamless. Image matching is one of the core problems in computer vision and digital photogrammetry. Traditionally, interest point detectors such as the Harris operator (Harris and Stephens, 1988) and the Förstner operator (Förstner and Gulch, 1987) have been used widely in stereo-image matching. In the last decade, wide-baseline matching has been an active area of research in the computer vision community. A variety of invariant detectors and descriptors have been proposed for wide-baseline matching, object recognition, and image retrieval purposes including affine invariant regions (Tuytelaars and Van Gool, 2000), MSER (maximally stable extremal regions) (Matas et al., 2002), Harris-Laplace and Harris-Affine interest-point detectors (Mikolajczyk and Schmid, 2004), SIFT (Scale Invariant Feature Transform) (Lowe 1999 and 2004), and SURF (Speeded-Up Robust Features) (Bay et al., 2008). These detectors and their Photogrammetric Engineering & Remote Sensing Vol. 77, No. 6, June 2011, pp. 609–618. 0099-1112/11/7706–0609/

A Self-Calibration Bundle Adjustment Method for Photogrammetric Processing of Chang

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