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Research on Geometric Rectification of High Resolution Remote Sensing Imagein Forest Areas

Author: ZhongXiaoMing
Tutor: JiaJianHua；LiChongGui
School: Xi'an University of Science and Technology
Course: Cartography and Geographic Information Systems
Keywords: The line Pushbroom image High Resolution Satellite Imagery Universal correction model Strict imaging model Geometric correction
CLC: TP751
Type: Master's thesis
Year: 2011
Downloads: 69
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Abstract


With the development of remote sensing technology, high-resolution remote sensing images have been widely used in forestry. Remote sensing satellite imaging, remote sensing satellite images are subject to a variety of factors and geometric distortion occurs, it is necessary to achieve precise geocoding image geometric correction, for subsequent geometric measurements are compared with each other and composite analysis support. In the the traditional photogrammetry field, the application of more physical model. This model processing technology has matured, the positioning accuracy is relatively high. However, due to the physical sensor model involves the sensors physical structure, the imaging method, and a variety of imaging parameters. Ordinary users can not get this information, it can only use common geometric correction model for processing of remote sensing images. QuickBird image for a scene in Shenzhen, discusses the high-resolution remote sensing images of a variety of common geometric correction model and its solution method, and factors affecting forest areas high-resolution remote sensing image geometric precision correction accuracy to do the research, Based on this analysis of the deformation law of the forest areas of high resolution remote sensing images. The main conclusions are: (1) in all common geometric precision correction model, the correction accuracy of the rational function model is the highest, but the more rational function model requires the number of control points, and the model solver accuracy depends on the control points distribution. (2) the accuracy of the polynomial model by undulating terrain influence, to improve the accuracy of the polynomial model with the order of the polynomial changes, the terrain is very small, improvements choose the right order polynomial model can obtain a higher geometric correction accuracy. (3) in three a direct linear transformation model, a direct linear transformation of the self-calibration model checking little bit error is minimized, and the use of a small amount of ground control points operator will be able to obtain a stable solution results. (4) select a particular approach to forest areas high-resolution remote sensing image geometric correction, it should be considering the accuracy of the algorithm complexity of known data requirements and other factors. (5) forest areas with high spatial resolution remote sensing imagery geometric precision correction, improved polynomial model of high precision, small amount of calculation, the number of control points and the spatial distribution of low requirements, it is a good approximation of geometric correction algorithm . (6) forest areas of high-resolution remote sensing image distortion is affected by topography, geometric correction should take full account of the terrain factors.

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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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