Aerial sensors are widely used to acquire imagery for photogrammetric and remote sensing application. In general, the images have large overlapped region, which provide a lot of redundant geometry and radiation information for matching. This paper presents a POS supported dense matching procedure for automatic DSM generation from aerial imagery data. The method uses a coarse-to-fine hierarchical strategy with an effective combination of several image matching algorithms: image radiation pre-processing, image pyramid generation, feature point extraction and grid point generation, multi-image geometrically constraint cross-correlation (MIG3C), global relaxation optimization, multi-image geometrically constrained least squares matching (MIGCLSM), TIN generation and point cloud filtering. The image radiation pre-processing is used in order to reduce the effects of the inherent radiometric problems and optimize the images. The presented approach essentially consists of 3 components: feature point extraction and matching procedure, grid point matching procedure and relational matching procedure. The MIGCLSM method is used to achieve potentially sub-pixel accuracy matches and identify some inaccurate and possibly false matches. The feasibility of the method has been tested on different aerial scale images with different landcover types. The accuracy evaluation is based on the comparison between the automatic extracted DSMs derived from the precise exterior orientation parameters (EOPs) and the POS.
Remote sensing images usually need scale-up for visualization or representation, using only one original image. According to the performance of detective sensors, a new and more applicable method is proposed here. To enhance the high-frequency components, the modulation transform function compensation (MTFC) part focuses on how to adjust the spatial response before and after launch, under signal-to-noise ratio control. This largely reduces the ring phenomenon from incorrect point spread function guesses. Then a contour stencil prior manages to limit edge artifacts in the upscaled image after MTFC. An iterative backprojection operation with fast convergence is also utilized to bring about intensity and contour consistency. We finally present our analysis based on real images with parallel design for full speed. Compared with existing algorithms, the operator illustrates its potential to keep geometric features and extend the visual and quantitative quality for further analysis.
As a way of acquiring elevation with high accuracy, space-borne laser altimeter improves the capability of 3-dimensional cartography of satellite optical remote sensing imagery. However, the plane accuracy of space-borne laser altimeter is not so high as its elevation accuracy. Accordingly, the error souses and their influences on space-borne laser altimeter ground positioning are studied in this paper. The space-borne laser altimeter is very different from classical photogrammetry, the elevation information is obtained by measuring the time between sending and receiving the laser. As space-borne laser altimeter supplies laser echo signal other than image, the positioning accuracy is more important as well as the exterior orientation elements. The ground positioning of space-borne laser altimeter is first modeled, then error propagation of the model is studied, and the main error souses of space-borne laser altimeter ground positioning are obtained. At last the influences of each error souse on space-borne laser altimeter ground positioning are analysed as the references for space-borne laser altimeter designing and application.