Accuracy Analysis of Generalized Imaging Models for QuickBird Stereo Imagery
ABSTRACT This paper analyzes the accuracies of different generalized imaging models (but RFM) for a separate-orbit QuickBird stereo imager pair, including extended DLT model, parallel projection model, projection-modified affine model, parallel perspective model, time-variant-parameterized affine model and the proposed time-variant-parameterized parallel perspective model. The experimental results have revealed the spatial dynamic characteristic of the QuickBird sensor. Due to the continuous re-orientation of the sensor, imaging models with constant parameters such as extended DLT model and affine projection model, can not describe the imaging geometry of the QuickBird imagery sufficiently. By contrast, imaging models with time-variant parameters perform much better. Meanwhile, the parallel perspective model with time-variant parameters shows superiority to the time-variant-parameterized affine model. With no less than 14 ground control points, parallel perspective model with time-variant parameters can provide the accuracy of sub-pixel level, which is close to that achieved by the more rigorous RFM.
Article: Sensor orientation via RPCs[show abstract] [hide abstract]
ABSTRACT: The adoption of rational functions as a preferred sensor orientation model for narrow field of view line scanner imagery accompanied the introduction of commercial high-resolution satellite imagery (HRSI) at the turn of the millennium. This paper reviews the developments in ground point determination from HRSI via the model of terrain independent rational polynomial coefficients (RPCs). A brief mathematical background to rational functions is first presented, along with a review of the models for generating RPCs from a rigorous sensor orientation, and for geopositioning via either forward intersection or monoplotting. The concept of RPC block adjustment with compensation for exterior orientation biases is then discussed, as is the means to enhance the original RPCs through a bias correction procedure. The potential for RPC block adjustment to yield sub-pixel geopositioning accuracy from HRSI is illustrated using results from experimental testing with two Quickbird stereo image pairs and three multi-image IKONOS blocks. Finally, error propagation issues in RPC block adjustment of HRSI are considered.ISPRS Journal of Photogrammetry and Remote Sensing. 01/2006;
- Geoscience and Remote Sensing Symposium, 2005. IGARSS '05. Proceedings. 2005 IEEE International; 08/2005
Conference Proceeding: Linear Pushbroom Cameras.[show abstract] [hide abstract]
ABSTRACT: Modelling and analyzing pushbroom sensors commonly used in satellite im- agery is difficult and computationally intensive due to the motion of an orbiting satellite with respect to the rotating earth, and the non-linearity of the mathematical model involv- ing orbital dynamics. In this paper, a simplified model of a pushbroom sensor (the linear pushbroom model) is introduced. It has the advantage of computational simplicity while at the same time giving very accurate results compared with the full orbiting pushbroom model. Besides remote sensing, the linear pushbroom model is also useful in many other imaging applications. Simple non-iterative methods are given for solving the major standard photogrammetric problems for the linear pushbroom model: computation of the model parameters from ground-control points; determination of relative model parameters from image correspon- dences between two images; and scene reconstruction given image correspondences and ground-control points. The linear pushbroom model leads to theoretical insights that are approximately valid for the full model as well. The epipolar geometry of linear pushbroom cameras in investigated and shown to be totally different from that of a perspective camera. Nevertheless, a matrix analogous to the fundamental matrix of perspective cameras is shown to exist for linear pushbroom sensors. From this it is shown that a scene is determined up to an affine trans- formation from two views with linear pushbroom cameras.Computer Vision - ECCV'94, Third European Conference on Computer Vision, Stockholm, Sweden, May 2-6, 1994, Proceedings, Volume I; 01/1994