Photogrammetria最新文献

A programme of work has been carried out at University College London with support from other mapping organisations in the UK to determine the amount of information which can be extracted from TM and SPOT in comparison with a variety of map scales, and in a variety of different types of area. Detailed plots from multispectral, panchromatic and stereo imagery have been compiled, and compared with available map data. The results from these experiments are presented.

The further development of remote sensing applications depends on an enhanced dialogue between those who master the technique of remote sensing and the ultimate users. A correct balance between the technology push and the market pull is not always easy to strike in this area. Within the Commission of the European Communities, services are working together on the one hand, on implementation of policies related to agriculture, environment, assistance to developing countries, regional development and raw materials and, on the other hand, on JRC research to promote new applications of remote sensing. These concerted efforts have led to successful results which clearly establish the benefits derived from each observation from space, for certain sectors of socio-economic relevance.

The traditional edge extraction process has five basic stages: smoothing, edge detection, thresholding, thinning and linking. All of these stages require different algorithms to carry out their functions, which have typically required artificial limits or constraints set by “heuristics”. This research has designed and implemented an automated technique for edge extraction that has consistent logic linking the various stages of detection and formation, in which artificial limits have been avoided. A wide range of filters and detectors were evaluated in both the spatial and frequency domains, as well as operators using both rate-of-change and orientation criteria. For smoothing, a minimum-variance filter produced the most accurate and reliable results. The best method of edge detection was identified as one of the derivative filters. For thinning and linking, the definition of an edge was most accurate if the orientation of the edge was the prime consideration. These methods produce results which efficiently extract edges for both boundaries and linear features, are relatively tolerant of noise in the data, and utilize a logical set of rules that can be adapted as the data dictate.

In quality analysis, optimization design and blunder detection of many photogrammetric problems, repeated computation of reliability matrix QvvP is often required. In this paper, a new recursive method for repeated computation of QvvP is developed. From a test on a bundle block adjustment, it is shown that this new method posesses much higher computational efficiency than the conventional methods.

In a bundle adjustment, the imaging configuration is an important factor in computing the accuracy of the object points. The theory of optimizing network configuration is applied to photogrammetry. For application to imaging, camera stations are shifted in order to improve the precision of object-point determination by improved intersections of rays. A criterion matrix is used as a target function in the optimization process. This matrix is constructed as an ideal covariance matrix that demands homogeneous and isotropic errors. The optimization process approximates the real covariance matrix of the network to the ideal criterion matrix by means of small shifts of the camera stations. The approximation is performed by a least-squares process which minimizes the discrepancies between the real covariance matrix of a given starting configuration, and an ideal, constructed criterion matrix.