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Research on Super-resolution Reconstruction from Passive Millimeter Wave Image

Author: GuoHaiLei
Tutor: TianYan
School: Huazhong University of Science and Technology
Course: Communication and Information System
Keywords: Millimeter wave imaging Super-resolution Point spread function Iteration projection Scale Invariant Feature Transform Image registration Sub-pixel
CLC: TP391.41
Type: Master's thesis
Year: 2009
Downloads: 29
Quote: 0
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Abstract


Millimeter wave with respect to the microwave band , as the wavelength is shorter , it is possible to obtain a higher spatial resolution and accuracy ; band available wide band having penetrate clouds , fog, smoke and dust , and is able to penetrate the plasma , thus work around the clock in harsh environments ; millimeter wave good confidentiality , strong anti-jamming capability ; millimeter-wave effective detection metal material and stealth materials . Based on the above advantages , passive millimeter wave imaging has a wide range of military and civilian prospects . But passive millimeter wave image relative to the optical image , the resolution is very low, which greatly affect the performance of millimeter-wave imaging applications . Research the super-resolution technology to improve the spatial resolution of the millimeter-wave images , this has important theoretical significance and practical value to make up for the lack of hardware or reduce the cost of access to high-resolution millimeter wave image . Firstly, the system introduces the development status of passive millimeter wave technology at home and abroad , and the super-resolution technology , reviewed the development of passive millimeter wave image super-resolution technology ; then discusses the main factors of passive millimeter wave image degradation ; in Based on this , the disc defocus and Gaussian defocus two image degradation mode parameter estimation method . For the disc the defocusing degradation situation , the use of the degradation parameter estimation method based on the Laplace operator ; Gaussian edge spread function based the defocus parameter estimation method and parameter estimation for Gaussian degenerate influencing factors were analyzed , draw some qualitative conclusions . Estimated on the basis of the parameters of image degradation , a single image through the introduction of improved non - linear operation factor , and on the nonlinear the Jansson-vanSitter algorithm improvement; paper also proposed a high - frequency prediction and inverse weighting two against mm wave image resolution enhancement algorithms ; the final combined neural network and improved nonlinear the Jansson-vanSitter algorithm to achieve a single image super-resolution reconstruction . Registration algorithm for multi - frame image super-resolution problem through an improved scale invariant feature transform , to achieve sub-pixel level registration of multi - frame image fusion based on multi-frame image , and non- fused image using the improved linear the Jansson-vanSitter algorithm , multi-frame super-resolution image reconstruction .

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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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