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Due to the limited pixel numbers in single TDI CCD chips, some TDI CCD chips are combined in the focal plane to reach a sufficient swath width. Basic imagery is delivered as one image data file per strip and how to convert those sub-images to a larger, accuracy equivalent image is an essential problem in satellite images’ processing. Some key factors that affect the imaging quality of TDI CCD images are discussed firstly. It shows that discrepancies in the along-track direction which caused by different viewing angle and topographic relief are the main problem to improve the stitching accuracy. Three basic image-oriented stitching strategies are discussed. Experimental results show that the RMS of shift transformation, single affine transformation and piecewise affine transformation is 1.4 pixels, 1.3 pixels and 0.2 pixels. Piecewise affine transformation fully meets the requirements of further processing.

Traditional orthoimage mosaic methods do not perform well in computational speed and geometric precision. This paper proposed a fast orthoimage mosaic method for the application of grid. First of all, down-sample the original images and extracts feature, and adopt SANSAC to estimate the relative initial homography; second, refine homography matrix by Levenberg-Marquardt method and use the sparse bundle adjustment method to estimate the precise homography matrix; Third, passed the homography matrix to the original level of image by the homography relationship of the down-sampling and original image. Finally, synthesize the mosaic image. Our experiments showed that the method combined the down-sampling homography relationship of original image with sparse bundle adjustment organically, which effectively improved the speed and obtained geometric seamless mosaic.

The technologies of traffic information collection based on GPS equipped floating car have been become one of the main important means for real-time collecting traffic information in intelligent transportation system. So, the electronic map of route network is important to collect traffic information. As present, the link dividing methods can’t take into account the different conditions of traffic flow and the different attributes of the route. This paper presents a novel link dividing method: Firstly, the speed of the floating car history track is regarded as a stochastic and its frequency spectrum is obtained using Fourier transform; Secondly, the optimal sampling intervals of the link dividing are obtained using the frequency spectrum of speed and Shannon sampling theory; Finally, the novel link dividing model is founded based on the optimal sampling intervals and the attributes of the routes. This method not only considers the different conditions of traffic flow, but also distinguishes the different traffic flow of the different places of a link, which can improve application effect of the route traffic conditions and vehicle dynamic navigation.

Generally, traditional maps used in navigation are vector maps. This kind of map is rather poor in visual effects, and it’s updated quite slowly, which can not satisfy users’ requirement. This paper puts forward the concept of using remote sensing Images for navigation and does some research on the most critical Image management technology. We describe a new data organization method(Time-Quad-R-Tree) which is fit for the Image navigation. The experiments show that the method can satisfy the up-to-date demand of Image navigation.

Efficient and reliable map-matching algorithms were essential for vehicle navigation systems. Most existing solutions can’t provide trustworthy outputs when the situation was ambiguous (such as at road intersections). Put forward to map matching according to pseudo-Zernike moments. The new Algorithm leads, pseudo-Zernike moments to describe track curve into pseudo-Zernike moments on this foundation of shape, revised a mistake result further. Pass to imitate true and on trial express, the new calculate way has stronger usefulness and credibility under the complicated environment.