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Study on Virtual Detector of Infrared Hyper-Spectral Image

Author: WangChengAn
Tutor: TanHePing
School: Harbin Institute of Technology
Course: Engineering Thermophysics
Keywords: hyperspectral image neural network method fusion far infrared channel target recognition
CLC: TP391.41
Type: Master's thesis
Year: 2008
Downloads: 86
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Abstract


High performance detection equipment needs target signal characteristic value which is much preciser and contains a larger amount of data in order to detect dim targets and camouflaged targets. Hyperspectral information has the advantage of high spatial and spectral resolution, so this spatial and spectral characteristics can be used to distinguish dim targets in complex background with higher credibility. With the rapid development of numerical simulation, the virtual design will be gradually used in the field of aerospace technology as a new comprehensive subject. It can reduce the research cost greatly, improve the accuracy and shorten the period of development.This dissertation focuses on the simulation of the background and target in far infrared channel (8~12μm ) and the detection of target in background. The main contents of this dissertation are as follows:1.The hyperspectral image is got by the simulation and calculation of background. Calculation process includes the generation of natural terrain and background, the solution of surficial temperature model and the atmosphere influence on radiation transfer.2.The infrared radiation properties of exhaust plume is modeled by heat flux method. Once they are added in the energy field of background, we could get the hyperspectral image (8~12μm ) in which the background contains target.3. The energy ratio of the target and background is calculated and then the band is selected to distinguish target. Dim targets in complex background are distinguished by neural network method and we get the best spectrum band combination and the LS_SVM method to distinguish them.4. The information correlation of the hyperspectral images is quantitated between the band of 80 and 106 by calculating the correlation information entropy. The hyperspectral images with stronger correlation between each other are processed by fusion method. LS_SVM method is used to distinguish dim targets in hyperspectral images before and after fusion. The calculation results show that it can be effective to distinguish target and realize the image compression by using the fusion method.This dissertation realizes the hyperspectral image simulation in the far infrared channel in the numerical method and focuses on target recognition problem when the target is in the natural background. The method developed in this dissertation can present practial process factually. The simulation effect is good and the method developed in the dissertation is feasible.

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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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