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Wide angle view of multi-view panorama construction

Author: ZhaoPin
Tutor: ZhouYue
School: Shanghai Jiaotong University
Course: Pattern Recognition and Intelligent Systems
Keywords: Wide-angle image correction Image Registration Image Stitching Image Fusion
CLC: TP391.41
Type: Master's thesis
Year: 2009
Downloads: 75
Quote: 1
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Abstract


Image correction, image mosaic and panorama building is very basic computer image processing applications is also very important, but also a research hotspot in recent years, imaging technology. Image mosaic and panorama image construction to expand horizons for effective and efficient information access has a very important significance. In the camera's image processing technology, automotive electronics and mobile phones and other mobile communications devices have a wide range of applications. Currently, the use of wide-angle image correction is larger image pinhole model. Although no projection pinhole model wide-angle lens has a better correction effect, but with fisheye wide applications due to the inherent fisheye projection principle, the pinhole model for fisheye correction is not ideal. To solve this problem, this paper uses a universal camera model. The image stitching technology is the technology developed in recent years a larger image. Previous image stitching technology because there is no automatic matching method often requires human interaction, greatly reducing the efficiency of the algorithm. And in recent years, such as image registration technology, image matching method allowing to develop and build automatic image stitching panoramas possible. In this paper, image mosaic using saliency detection region matching method, and on this basis the image projection and stitching. The main work includes: image registration algorithms, image stitching algorithm as an important pre-processing, image registration point corresponds to the quantity and exact traveling directly affect splicing results. Therefore, this paper has done a lot in image registration work, including regional saliency detection, in order to improve the speed of the algorithm and the importance of matching points. sift algorithm registration, in order to obtain valuable feature point matching related. Mismatch removal, thereby reducing the number of false matches in order to improve accuracy of the algorithm. Thus, the algorithm of the image obtained at a rate faster more accurate correspondence between points. Stitching Algorithm for the next do a good preparation. Image stitching algorithm, accurate matching points, the corresponding feature point based on correlation. Using the least squares method to obtain the most single map projection mapping. Reuse single map map projection of the image will be two images projected onto the same coordinate system. Finally, using the interpolation method to construct the initial mosaic images. Image fusion algorithm, on the preliminary results of using the weighted average method spliced: Use the weighting function to the weighted average of overlapping frames corresponding to each pixel. Smooth transition area on the center of the image overlap. Right distance from the boundary of the pixel pitch. This function is the lowest edge of the image, while the maximum contribution at the center.

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
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