Edward M. Mikhail

Detection and sub-pixel location of photogrammetric targets in digital images☆

Abstract Data consist of aerial digital images with ground targets in the form of crosses of different dimensions and orientations. Location and recognition of the targets relies on Fourier descriptors and on two-dimensional moments. Further processing employs least squares adjustment of the target shape in order to precisely determine the position ( X and Y ) and orientation θ of each cross to a fraction of a pixel accuracy. Results are given from tests with synthetic crosses on a real terrain digital data base. Accuracies achieved have reached to within 0.03–0.05 pixel. Digital image compression has shown to cause cross targets to shift in location by as much as 0.5 pixel.

Extracting Urban Road Networks from High-resolution True Orthoimage and Lidar

Automated or semi-automated feature extraction from remotely collected, large scale image data has been a challenging issue in digital photogrammetry for many years. In the feature extraction field, fusing different types of data to provide complementary information about the objects is becoming increasingly important. In this paper, we present a newly developed approach for the automatic extraction of urban area road networks from a true orthoimage and lidar assuming the road network to be a semi-grid pattern. The proposed approach starts from the subdivision of a study area into small regions based on homogeneity of the dominant road directions from the true orthoimage. Each region’s road candidates are selected with a proposed free passage measure. This process is called the “acupuncture” method. Features around the road candidates are used as key factors for an advanced “acupuncture method” called the region-based acupuncture method. Extracted road candidates are edited to avoid collocation with non-road features such as buildings and grass fields. In order to produce a building map for the prior step, a first-last return analysis and morphological filter are used with the lidar point cloud. A grass area thematic map is generated by supervised classification techniques from a synthetic image, which contains the three color bands from the true orthoimage and the lidar intensity value. Those non-road feature maps are used as a blocking mask for the roads. The accuracy of the result is evaluated quantitatively with respect to manually compiled road vectors, and a completeness of 80 percent and a correctness of 79 percent are obtained with the proposed algorithm on an area of 1,081,600 square meters.

Linear features for photogrammetric restitution and object completion

Rigorous formulation in terms of only feature descriptors is given for: two- and three- dimensional transformations, photogrammetric conditions, and linear feature geometric constraints. Experimental results, considering control and pass features, from single photo resection (recovering both interior and exterior orientation elements) and two-photo triangulation (estimating pass lines for object completion), using simulated data and some real image data. Geometric constraints are used to provide redundancy in place of straight lines in stereo pairs. Extensive investigation is continuing.

Photogrammetric analysis of image invariance

Basic invariance theory for frame photography has existed in the photogrammetric literature for over a century. It has been recently rediscovered and significantly extended by researchers in computer vision (CV) and image understanding (IU). It is applied to problems involved in image transfer and object recognition and reconstruction, among others. Research is in progress at our Photogrammetric Analysis Laboratory, to analyze various image invariance techniques, for both 2D and 3D objects, particularly with regard to their accuracy and reliability. Existing well established photogrammetric techniques, as well as modifications thereto, are evaluated as both equivalent and complementary methods to invariance. Relationships are investigated between the imaging parameters and the variables involved in invariance, which usually combine such parameters together. Rigorous unified least squares is used in cases of redundancy and constraints. Results show significant improvement in accuracy and robustness as compared to direct linear techniques generally used in the CV/IU literature.

Spatial analysis of image registration methodologies for fusion applications

Data registration is the foundational step for fusion applications such as change detection, data conflation, ATR, and automated feature extraction. The efficacy of data fusion products can be limited by inadequate selection of the transformation model, or characterization of uncertainty in the registration process. In this paper, three components of image-to-image registration are investigated: 1) image correspondence via feature matching, 2) selection of a transformation function, and 3) estimation of uncertainty. Experimental results are presented for photogrammetric versus non-photogrammetric transfer of point features for four different sensor types and imaging geometries. The results demonstrate that a photogrammetric transfer model is generally more accurate at point transfer. Moreover, photogrammetric methods provide a reliable estimation of accuracy through the process of error propagation. Reliable local uncertainty derived from the registration process is particularly desirable information to have for subsequent fusion processes. To that end, uncertainty maps are generated to demonstrate global trends across the test images. Recommendations for extending this methodology to non-image data types are provided.

Automation in photogrammetry: Recent developments and applications (1972–1976)☆

Abstract An overview of recent developments in the automation of photogrammetry in various countries is presented. Conclusions regarding automated photogrammetry reached at the 1972 Congress in Ottawa are reviewed first as a background for examining the developments of 1972–1976. Applications are described for each country reporting significant developments. Among fifteen conclusions listed are statements concerning: the widespread practice of equipping existing stereoplotters with simple digitizers; the growing tendency to use minicomputers on-line with stereoplotters; the optimization of production of digital terrain models by progressive sampling in stereomodels; the potential of digitization of a photogrammetric model by density correlation on epipolar lines; the capabilities and economic aspects of advanced systems which permit simultaneous production of orthophotos, contours, and digital terrain models; the economy of off-line orthophoto systems; applications of digital image processing; automation by optical techniques; applications of sensors other than photographic imagery, and the role of photogrammetric phases in a completely automated cartographic system.

Holograms And Holographic Stereomodels: Their Mensuration And Mapping

The relative ease with which three-dimensional images are reconstructed from single hologram plates makes them an attractive alternative to the photogrammetrist for mensuration and mapping of close-range objects. For accurate metric work, the reconstruction geometry must be recovered to with-in fine tolerances, the values of which are given. A simple scheme for extracting positional information from holograms, as well as performing graphic and digital mapping, is explained and sample results included. To extend the capability to topographic terrain applications from aerial photography, the concept of the Holographic Stereomodel (HS), both fresnel and focused image types, is explained and relative advantages and disadvantages enumerated. The photogrammetric and geometric problems involved in the production of HS are expounded upon. Mensuration and mapping considerations from HS together with results obtained to-date are given.

Principles and Evaluation of Autostereoscopic Photogrammetric Measurement

Stereoscopic perception is a basic requirement for photogrammetric 3D measurement and accurate geospatial data collection. Ordinary stereoscopic techniques require operators wearing glasses or using eyepieces for interpretation and measurement. However, the recent emerging autostereoscopic technology makes it possible to eliminate this requirement. This paper studies the principles and implementation of autostereoscopic photogrammetric measurement and evaluates its performance. We first describe the principles and properties of the parallax barrier-based autostereoscopic display used in this study. As an important metric property, we quantitatively present the autostereoscopic geometry, including viewing zones and the boundary of a viewer’s movement for autostereoscopic measurement. A toolkit AUTO3D is developed that has common photogrammetric functions. The implementation principles are described by addressing the differences compared to the ordinary stereoscopic technology. To evaluate the performance of the autostereoscopic measurement, images at a resolution of 25 � m and 50 � m are measured by a group of seven (7) operators, who are asked to digitize 18 well-defined roof points and 18 ground points. These results are evaluated by comparing the same measurements obtained from a popular stereoscopic photogrammetric workstation. It is shown that the precision of autostereoscopic measurement is about 16 percent to 25 percent lower than the conventional stereo workstation.

Object model construction by invariance and photogrammetry

Several recent invariance techniques such as: trilinearity (trifocal tensor), cross-ratio of planes, BC-invariant, and factorization of the fundamental matrix, have been extensively analyzed. Significant characteristics which distinguish them from equivalent photogrammetric techniques have been determined and assessed. Test results from simulated and real data, particularly related to the construction of imaged objects, are presented. These are in turn compared to results obtained from photogrammetry. Conclusions are drawn particularly with respect to the relative performance of the various methods, and recommendations made for continuing research.

Comparison between invariance and photogrammetry for image and object transfer

Point- and line-based invariance methods are used for both image and object transfer 2D planar objects. Invariance yields equations of straight lines the intersections of which give the positions of the points to be transferred. For non-redundant 4-point invariance, the sequence of points used yields line pairs of different geometric strengths. In redundant cases, using different point sequences to form linear condition equations results in least squares estimates which are different for both the positions and their quality. Corresponding photogrammetric techniques based on point and line features, on the other hand, provide unique estimates and covariances for both non-redundant and redundant cases. A refined least squares approach, for which the linear invariance equations become non-linear, appears to alleviate the non- uniqueness problem. Point-based image invariance is investigated for 3D objects in multiple images. The concepts of the essential and fundamental matrices for use with calibrated and uncalibrated cameras, respectively, are presented. The use of the fundamental matrix to transfer images from two photographs to a third is described and early results summarized. Introducing a constraint on the fundamental matrix stabilizes the solution, which otherwise leads to widely varying results. Preliminary results from linear invariance based object point transfer suggest that the uniqueness problem arising from point sequences also exists in this task. Research is continuing to resolve this issue and to provide photogrammetric equivalent and complimentary methods to invariance.