ASPRS

PE&RS August 2001

VOLUME 67, NUMBER 8
PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING
JOURNAL OF THE AMERICAN SOCIETY FOR PHOTOGRAMMETRY AND REMOTE SENSING

Peer-Reviewed Articles

909 Single-Photo Resection Using the Modified Hough Transform
Ayman Habib and Devin Kelley

Abstract
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The single-photo resection (SPR) has been a fundamental task in many photogrammetric, remote sensing, and computer vision applications. The objective of the SPR is to determine the position of the perspective center and the orientation of the image coordinate system relative to the ground coordinate system (i.e., establish the exterior orientation parameters, or EOP). In traditional photogrammetric techniques, this problem is solved using 2D image point to 3D object point correspondence. Recent advances in digital photogrammetry mandate adopting higher order control features (e.g., linear features). Also, one should attempt to solve this problem without knowing the correspondence between the image and object space features. This approach is used to estimate the parameters of a mathematical model relating the entities of two data sets when the correspondence of entities is unknown. As a result of the parameter estimation, the correspondence is implicitly determined. This technique has been applied to the single-photo resection, where the collinearity model is used to relate extracted edge (feature) pixels in a digital image to 3D object space points along linear features. As a result of this approach, the six exterior orientation parameters are estimated and the correspondence between image and object space features is established. This technique facilitates the fusion of digital imagery with terrestrial mobile mapping data, GIS data, and line maps. In addition, automated matching facilitates the detection of changes between object and image space features. It has to be mentioned that this approach is robust against discrepancies between the object space control features and the image space extracted features. Only common features are used for the parameter estimation. On the other hand, non-corresponding features will not affect the quality of the estimated parameters.

915 Radiometric Corrections for Multispectral Airborne Video Imagery
A. Edirisinghe, G.E. Chapman, and J.P. Louis

Abstract
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Radiometric fidelity of calibrated airborne video imagery is important if the imagery is to be used for quantitative analysis of target surfaces. A four-channel Multispectral Airborne Video System (MAVS) is used at Charles Sturt University (CSU) for a range of environmental and agricultural monitoring applications. The radiometric distortions in the MAVS imagery could occur because of lens characteristics in the form of vignetting effects and optical aberrations. This paper details the control experiments conducted to detect and quantify such distortions. The vignetting in particular is shown to be creating a non-uniform brightness level across the MAVS imagery. The paper then develops efficient procedures to correct the vignetting in the MAVS imagery by producing relevant correction coefficients, templates, and equations. The accuracy of these de-vignetting (correction) procedures is shown to be comparable to the accuracy of similar corrections reported elsewhere. An investigation into the effect of spectrum related vignetting on the MAVS imagery due to spectral filter characteristics found negligible distortions that did not warrant corrections. This particular type of vignetting is usually caused by the wavelength shifts in the band-pass window of a filter at large incident angles.

925 On Preserving Spectral Balance in Image  Fusion and Its Advantages for Geological  Image Interpretation
Ernst M. Schetselaar

Abstract
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The merging of multisource remotely sensed data has become a widely used technique to take advantage of complementary data sets in image interpretation. A fundamental problem in its application is how the transformations between perceptual and display device dependent color spaces are implemented in addressing the attributes of human color perception intensity (I), hue (H), and saturation (S) in an optimal and unambiguous manner. This paper presents a method that preserves the spectral balance of the multispectral image data and modulates the IHS coordinates uniformly. This method takes the limits in the representation of color of the display device into account, which aids in compromising the amount and spatial distribution of over-range pixels against contrast in intensity and saturation. Two processing examples are provided to illustrate the advantages of this method for geological mapping. In the first example, Landsat TM bands 7, 3, and 1 are integrated with an aerial photograph to map lithological units in metamorphic basement and its sedimentary cover. In the second example, K, eTh, and eU gamma-ray spectrometry and Landsat TM data are integrated to map compositional and structural patterns within a granite batholith.

935 Unveiling the Lithology of Vegetated Terrains in Remotely Sensed Imagery
Robert E. Crippen and Ronald G. Blom

Abstract
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" Forced invariance" is a processing method that can subdue the expression of vegetation and enhance the expression of the underlying lithology in remotely sensed imagery. Data for each spectral band are altered in an empirically derived manner so as to produce a refined band that largely excludes contrasts attributable to variations in vegetation abundance. This is accomplished by (1) correcting the data for the effects of additive path radiance, (2) statistically characterizing the relationship between the band data and a vegetation index, and (3) multiplying the band data as a function of the index so that the average band value is generally invariant across all index values. Comparison of original and processed color composite displays confirms the method's utility in unveiling rock patterns consistent with nearby well-exposed bedrock and alluvial patterns downslope, especially in areas of open canopy vegetation such as in mixed arid and semi-arid terrains.

947 Integration of Hyperspectral and IFSAR  Data for Improved 3D Urban Profile Reconstruction
P. Gamba and B. Houshmand

Abstract
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In this paper hyperspectral (AVIRIS) and radar (AIRSAR) aerial data acquired over urban environments are considered. The information available from each sensor was extracted and merged to improve the 3D profile reconstruction of builtup areas. Two classification schemes were evaluated for AVIRIS data clustering, while the effect of the radar view angle was considered in assessing the quality of the associated digital elevation models. A detailed analysis of what is possible to extract and to what extent these data are useful was also produced, considering precise 2D and 3D ground truth of the UCLA campus.

957 Model-Based Conifer-Crown Surface Reconstruction from High-Resolution Aerial Images
Yongwei Sheng, P. Gong, and G.S. Biging

Abstract
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Knowledge of tree-crown parameters such as height, shape, and crown closure is desirable in forest and ecological studies, but those parameters are difficult to measure on the ground. The stereoscopic capability of high-resolution aerial images provides a method for crown-surface reconstruction. However, existing digital photogrammetry packages, designed to map terrain surfaces, cannot accurately extract tree-crown surfaces, particularly for conifer-crowns with steep vertical profiles. In this paper, we integrate crown features derived from images with stereo matching, and develop a model-based approach for reconstructing conifer-crown surfaces. The model is based on the fact that most conifer crowns are a form of solid geometry. We model a conifer crown as a generalized hemi-ellipsoid, establish the optimal tree model using a geometric equation, and apply the optimal tree model to guide a conventional pyramidal image matching in crown-surface reconstruction. The effectiveness of the approach is illustrated using an example of a redwood tree on 1:2,400-scale aerial photographs.

967 A Spatio-Temporal GIS Database for Monitoring Alpine Glacier Change
Jeremy L. Mennis and Andrew G. Fountain

Abstract
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Monitoring alpine glacier change has many practical and scientific benefits, including yielding information on glacier-fed water supplies, glacier-associated natural hazards, and climate variability. This paper describes the design and implementation of a spatio-temporal GIS database for monitoring glacier geometry and geometric change. The temporal component of the glacier data is managed through both a "snap-shot" and time-normalization approach to the relational data model in which glacier properties are organized according to their spatial and temporal dependencies. Because of the integration of diverse historic and contemporary data sources, metadata play a key role in managing data quality. For the initial population of the database, historic and contemporary map data on six glaciers on Mount Rainier, Washington were used to model glacier geometry and were examined for geometric change over the period 1913-1971.
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