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Edge Detection Of Remote Sensing Image Based On Data Field Model In Spectral Space

Posted on:2006-02-03Degree:MasterType:Thesis
Country:ChinaCandidate:N LiuFull Text:PDF
GTID:2120360182467509Subject:Photogrammetry and Remote Sensing
Abstract/Summary:PDF Full Text Request
Along with the advancement of Remote Sensing technology, the excellent ability of detecting hyper-spectral remote sensing spectrum makes the spectral response of electromagnetic wave represent the attributes of earth's surface objects more completely and truly and provide better platform for the interpretation of remote sensed images. During the information detection and discrimination, the remote sensed data always represents three important characters: space character, spectral character and time character. From the analysis of information theory, space character represents material information which exhibits the space geometric features such as the object's composition, structure, shape and size. And spectral character represents field information which shows the information including objects' energy and characteristic status. Time information represents the dynamic changing information which continues the space and spectral information and also includes surface features' time distribution and environmental factors about the climate. Based on material information, field information constructs remote sensed information after forming the regular system and method. Today, because of the constant increase of spectral resolution, it is difficult to the application of traditional image processing methods. The research of the feature extraction of hyper-spectral remote sensing data will be a very important way because it is about the process of information extraction and object identification.Image edge often is the most remarkable part of gray variance of image local area whose gray section may be seen a skip where the gray changes in a small area from low gray level to high gray level. Edge detection is very significant in the domain of image fragmentation, texture detection, computer view and so on. Although some traditional methods, such as differential template operators, artificial nervous network, wavelet analysis, expert system, mathematic morphology, genetic algorithm, are expanding the method system of edge detection, they almost have no ability to apply in the hyper-spectral data directly. For hyper-spectral images, the research contents have been changed from gray value to gray vector and from one-dimensional space to hyper-dimensional space. It is valuable to discover whether in the spectral space there are some new properties of edge points which can be regarded as gray non-continuous change in former viewpoint, and the way how to detect such properties.Data field is a kind of method of simulating field theory of physics. The main idea is that two data samples have some interaction which could be applied to represent the inner relationship between two data. Based on several fundamental concepts and terms, the idea of data radiation would be transplanted in the spectral space. Data radiation views any spectral vector point of the spectral space as an electric charge which owns some energy forming a data filed through radiating to the whole spectral space in order to affect other surrounding spectral vector points. The spectral vector point not only radiates its own energy to other points, but also receives the energy radiated from other vector points around it. There exits some invisible power between vector points. These points arenot lonely. The property of a vector point would not only been determined by the position in the spectral space, to some extent more importantly, by the radiation intensity of its surrounding vector points. The difference of distribution mode of surrounding spectral vector points makes the superposed radiation and energy different which represents the property of vector point different. It is the final goal to use the different energy of point in the data field presents the different property of the point. Data field theory views the local spectral vector points as a group in which every element interacts each other. The base of this paper is that a point's true property can be determined through calculating the field energy of point in a data field generated by this point's surrounding local vector points. Finally, we verify the reasonability and feasibility of the data field methods through MAIS 30 bands remote sensed images and TM 7 bands remote sensed images.
Keywords/Search Tags:hyper-spectral remote sensing, edge extraction, multi-scale detection, data field, data radiation, hyper-spectral information mining
PDF Full Text Request
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