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A Study on DSM-based Mosaicking Techniques for Remote Sensing Imagery

Author: JinJianLi
Tutor: FanYongHong
School: PLA Information Engineering University
Course: Photogrammetry and Remote Sensing
Keywords: Image stitching DSM Relative Radiometric Correction Water model Surface feature matching
CLC: TP751
Type: Master's thesis
Year: 2009
Downloads: 113
Quote: 1
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Abstract


With the rapid development of aerospace remote sensing technology , more and more high- resolution image data , image stitching demand more and more urgent . Automatic stitching as the automation of remote sensing image processing , in recent years become one of the focuses of the research in the field of remote sensing and photogrammetry . Automatic image stitching key technologies based on digital surface models (Digital Surface Model, DSM) made ??findings include: 1 . Relative radiometric correction algorithm based on HIS chroma adjustment . This method does not change the target image radiance case the sequence by converting the pixel RGB in HIS space chromaticity rotation , the correction of the target image relative radiation . Studies have shown that this method can effectively improve the visual consistency of the left and right images . Water model - based stitching line automatic extraction method . Based on the principle of water flow to the lower gravity , design stitching line automatically selects the rules ; This method is based on the the node relatively centerline , determine nodes in different locations around the right value , as a basis to select the next node ; elevation by detecting DSM Distinction between the consistency of the building . In order to avoid the stitching line coincides with the edge of the building and effectively circumvent the problem of poor building projected , morphological expansion DSM weights image processing , to ensure the effectiveness of automatic stitching line extraction . 3 . Overall matching algorithm based on the surface characteristics . The method polarizer select light directivity theoretical basis, using the binarized image , the logic operation of the pixel by pixel of the image of the overlapping area , looking extremum position , and determine a matching result . The robustness of the algorithm , and was able to match the image of the absence of point features .

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CLC: > Industrial Technology > Automation technology,computer technology > Remote sensing technology > Interpretation, identification and processing of remote sensing images > Image processing methods
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