Research On Key Technology Of True Orthophoto Generation Based On Aerial Images

Digital orthophoto(DOM) as an important basic geographic information products thathas both richly textures and geometric properties of the map, and its technology of productivehas been greatly evolved over the past few decades. The main purpose of DOM generationaims at eliminating projection distortion of terrain and camera tilt. We know thatorthorectified using for both orientation images and Digital Elevation Model(DEM), notinclude spatial object such as buildings that still exist the problem of projection distortion. Onthe other hand, with the development of digital camera technology, it has been able toacquired aerial images that resolution is less than0.1m, it means that the spatial object such asbuildings and bridges is very clearly in the images. The problem of both buildings tilt andocclusion will be yet existed if we are not considering these objects when orthorectifiedprocessing. As a result of there will be shown two mainly contradictions if the vector maps ofGIS are superimposed on to the DOM, firstly the buildings are acrossed by vector lines ofroads, and secondly vector outlines of the buildings cannot be fitted to itself. It will be loss thevalue of geo-referenced and cannot be used as a basic map if the problems of abovementioned are more seriously.True Orthophoto belongs to more advanced ortho products, and it is proposed in theabove context. The buildings and bridges are rectified to correct position in true orthophoto,and it will not be occluded other objects(such as roads). Both richly textures and geometricproperties of the map are really possessed by true orthophoto, so it has been widely concernedby lots of scholars of photogrammetry.The most significant difference between true orthophoto and DOM is visibility analysiswhen orthorectified processing. The textures of visible region are provided by grayinterpolation and assignment that is equivalent to tradition method of rectification. Thetextures of occluded region are repaired by visible parts of neighbour images. The visibilityanalysis is the most significant technology in the true orthophoto generating, it is also calledocclusion area detection. Now, the methods of visibility analysis that mainly making use ofDigital Surface Model and Digital Building Model are different according to various methodsof true orthophoto generation. As a result of this paper mainly aims at automatically obtainingDSM through image matching, and detecting occlusion areas through DSM or DBM, andgenerating true orthophoto by means of textures repairing.The main research contents areintroduced as follows:The matching algorithm of DSM is taken into account feature planars that have regional closure compared to feature points and edges, which is called Multiple Primitive Multi-ImageMatching. The matching of the feature planars can provide approximate value using formatching others points include feature points, grid points, key points of edges and boundarypoints of feature planars. The matching results of the boundary points of feature planars havevery high reliability, there can be served as 'anchor' using for point-line hybird globalconsistency matching with probability relaxation technique. On the other hand, a hugenumber of matching features through merging multiple matching primitives have ability toprovide dense, precise, and reliable results.An existence method of occlusion detection based on DSM is improved, and it has beenknown as Occlusion Detection based on Elevation Constraint. This method assumes fourDSM cells that are surrounding the nadir points are visible, and it detects the visibility of theDSM cells starting from the nadir point in a spiral mode from inside to outside.The occluded regions can be detected with the DBM, so-called Occlusion Detectionbased on TIN. The triangle is the detection unit in this method. Firstly, visual sorting oftriangles are primarily processed through inversing visual status of central projection.Secondly, it successively projects the triangles of sorted to image space, and projectionpolygons of image space can be constructed through merging all projection areas of triangles.The relationship between projection areas of triangles and projection polygons can be used fordetecting visual status.True orthophoto generation combines master image and slave images, and occludedregions are repaired through 'Weight Image', it means a quality measures in a so-calledweight, which is computed for each individual available slave images. Texture repair issimply picking the slave image with the highest weight.