&lt;title&gt;Adaptive automatic terrain extraction&lt;/title&gt;

Zhang, Bingcai; Miller, Scott

doi:10.1117/12.281065

Cited by 13 publications

(14 citation statements)

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“… Leica/Helava DPW, Automated Terrain Extraction (AATE), cross‐correlation (Miller and De Venecia, 1992; Zhang and Miller, 1997); Zeiss PHODIS ST, Topo SURF (MATCH‐T), feature based; Intergraph ImageStation, MATCH‐T, feature based (Krzystek, 1995); PCI Geomatics, DEM extraction; SOCET SET, BAE Systems digital DTM generation; and VirtuoZo, cross‐correlation with reshaping, global matching with probabilistic relaxation (Zhang et al, 1992, 1996). …”

Section: Time Of Consolidation and Extension (1990s)mentioning

confidence: 99%

Development and Status of Image Matching in Photogrammetry

Gruen

2012

The Photogrammetric Record

222

131

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Image and template matching is probably the most important function in digital photogrammetry and also in automated modelling and mapping. Many approaches for matching have evolved over the years, but the problem is still unsolved in general terms. This paper describes the development of image matching techniques in photogrammetry over the past 50 years, addresses the results of some empirical accuracy studies and also provides a critical account of some of the problems that remain. Although automated approaches have quite a number of advantages, the quality of the results is still not satisfactory and, in some cases, far from acceptable. Even with the most advanced techniques, it is not yet possible to achieve the quality of results that a human operator can produce. There is an urgent need for further improvements and innovations, be it through more powerful multi‐sensor approaches, thereby enlarging the information spectrum, and/or through advancements in image understanding algorithms, thus coming closer to human capabilities of reading and understanding image content.

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Section: Time Of Consolidation and Extension (1990s)mentioning

confidence: 99%

Development and Status of Image Matching in Photogrammetry

Gruen

2012

The Photogrammetric Record

222

131

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“…Slope analysis is also performed with (unreleased) software that reads ISIS image files. Our commercial digital photogrammetric workstation running SOCET SET (® BAE Systems) software [ Miller and Walker , 1993; 1995; Zhang and Miller , 1997] is used for “3‐D” processing steps such as control of the images and automatic extraction and manual editing of DTMs. SOCET SET includes a pushbroom scanner sensor model that is physically rigorous but “generic” enough (in the sense of allowing instrument parameters such as focal length and detector size to be specified in the image labels) to describe most MOC‐NA (and WA) images.…”

Section: Landing Site Selection and Moc Mappingmentioning

confidence: 99%

“…Results in bland areas were improved considerably by applying a difference‐of‐Gaussians (DOG) band‐pass filter [ Vosselman et al , 2004] to the images, followed by a contrast enhancement, for the final passes of the multiresolution, multipass matching strategy. The standard strategy for “adaptive” ATE [ Zhang and Miller , 1997] performs eight matching passes, beginning with images reduced in resolution by averaging of blocks of 32 × 32 pixels and ending with 2 × 2 averaged images. This strategy was applied to produce a DTM with 2‐m grid spacing based on the full resolution, unfiltered images.…”

Section: Hirisementioning

confidence: 99%

Ultrahigh resolution topographic mapping of Mars with MRO HiRISE stereo images: Meter‐scale slopes of candidate Phoenix landing sites

et al. 2008

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[1] The objectives of this paper are twofold: first, to report our estimates of the meter-todecameter-scale topography and slopes of candidate landing sites for the Phoenix mission, based on analysis of Mars Global Surveyor (MGS) Mars Orbiter Camera (MOC) images with a typical pixel scale of 3 m and Mars Reconnaissance Orbiter (MRO) High Resolution Imaging Science Experiment (HiRISE) images at 0.3 m pixel À1 and, second, to document in detail the geometric calibration, software, and procedures on which the photogrammetric analysis of HiRISE data is based. A combination of optical design modeling, laboratory observations, star images, and Mars images form the basis for software in the U.S. Geological Survey Integrated Software for Imagers and Spectrometers (ISIS) 3 system that corrects the images for a variety of distortions with single-pixel or subpixel accuracy. Corrected images are analyzed in the commercial photogrammetric software SOCET SET ( 1 BAE Systems), yielding digital topographic models (DTMs) with a grid spacing of 1 m (3-4 pixels) that require minimal interactive editing. Photoclinometry yields DTMs with single-pixel grid spacing. Slopes from MOC and HiRISE are comparable throughout the latitude zone of interest and compare favorably with those where past missions have landed successfully; only the Mars Exploration Rover (MER) B site in Meridiani Planum is smoother. MOC results at multiple locations have root-mean-square (RMS) bidirectional slopes of 0.8-4.5°at baselines of 3-10 m. HiRISE stereopairs (one per final candidate site and one in the former site) yield 1.8-2.8°s lopes at 1-m baseline. Slopes at 1 m from photoclinometry are also in the range 2-3°a fter correction for image blur. Slopes exceeding the 16°Phoenix safety limit are extremely rare.

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“…ATE uses an "inference engine" which adaptively generates image-matching parameters depending on facts such as terrain type, signal power, flying height or X and Y parallax. A user-given post spacing distance is used to control image correlation spacing (e.g., 2 m); hence, cross-correlation is not calculated for every image pixel (Zhang and Miller, 1997). We use the green, red and near-infrared bands of the sensor as input.…”

Section: Generation Of Summer and Winter Digital Surface Modelsmentioning

confidence: 99%

Snow depth mapping in high-alpine catchments using digital photogrammetry

Bühler¹,

et al. 2015

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Abstract. Information on snow depth and its spatial distribution is crucial for numerous applications in snow and avalanche research as well as in hydrology and ecology. Today, snow depth distributions are usually estimated using point measurements performed by automated weather stations and observers in the field combined with interpolation algorithms. However, these methodologies are not able to capture the high spatial variability of the snow depth distribution present in alpine terrain. Continuous and accurate snow depth mapping has been successfully performed using laser scanning but this method can only cover limited areas and is expensive. We use the airborne ADS80 optoelectronic scanner, acquiring stereo imagery with 0.25 m spatial resolution to derive digital surface models (DSMs) of winter and summer terrains in the neighborhood of Davos, Switzerland. The DSMs are generated using photogrammetric image correlation techniques based on the multispectral nadir and backward-looking sensor data. In order to assess the accuracy of the photogrammetric products, we compare these products with the following independent data sets acquired simultaneously: (a) manually measured snow depth plots; (b) differential Global Navigation Satellite System (dGNSS) points; (c) terrestrial laser scanning (TLS); and (d) ground-penetrating radar (GPR) data sets. We demonstrate that the method presented can be used to map snow depth at 2 m resolution with a vertical depth accuracy of ±30 cm (root mean square error) in the complex topography of the Alps. The snow depth maps presented have an average accuracy that is better than 15 % compared to the average snow depth of 2.2 m over the entire test site.

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<title>Adaptive automatic terrain extraction</title>

Cited by 13 publications

References 0 publications

Development and Status of Image Matching in Photogrammetry

Development and Status of Image Matching in Photogrammetry

Ultrahigh resolution topographic mapping of Mars with MRO HiRISE stereo images: Meter‐scale slopes of candidate Phoenix landing sites

Snow depth mapping in high-alpine catchments using digital photogrammetry

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