Dissertation > Excellent graduate degree dissertation topics show

Super-Resolution Reconstruction of Three-Line-Scanner Images

Author: FanChong
Tutor: GongJianYa;ZhuJianJun
School: Central South University
Course: Cartography and Geographic Information Engineering
Keywords: Three-Line-Scanner ADS40 PRISM Super-Resolution Image Registration Optical Flow
CLC: TP391.41
Type: PhD thesis
Year: 2007
Downloads: 427
Quote: 4
Read: Download Dissertation

Abstract


The Three-Line-Scanner camera can capture three images in the direction of looking forwards,downwards and backwards from the aircraft or satellite in the same time.So we can obtain three images in the same scene.In view of this,we present a maximum a posteriori estimation framework to obtain a high-resolution image from the Three-Line-Scanner images.According to the level of Three-Line-Scanner images,The superresolution process can be devided into two class.One is orthograph superresolution,the other is Level 1 image superresolution.The major work implemented are presented as follows:(1)The mathematics basis of superresolution technique and two model of it are discussed in detail.This paper also discusses the relationship between the superresolution technique and the inverse problems.Moreover,we present the computation method of the superresolution model.(2)This paper introduce the Image Registration mothed excluded aliased frequency domain into the super-resolution reconstruction of Level 1 TLS images.The algorithm can precisely estimate the image registration parameter by excluding aliased frequency domain of the low resolution images and killing the center part of the magnitude spectrum.In the same time,the keren sub-pixel registration method is discussed in detail.In order to overcome out its disadvantage. Moreover,this paper put forward a new improvement approach about keren method and its iterative method.The improvement approach base on the four parameters affine transformation model and abandon the rigid body transformation model.This change avoids the error that is brought on by the tailor series expandedness of angle and improves the precise of image registration.(3)This paper analyse the image capturing procedure of Camera and simulate the gaussian MTF of the static image captured by the Camera.we also introduce error-parameter method and GCV mothod to evaluate the Gaussian MTF of static images.In order to evaluate the MTF of remote sensing images whose MTF do not obey the Gaussian model,this paper introduce the edge method.However, Experimental results show that the error-parameter method and the edge method can not be used to supper-resolution reconstruction model because the MTF which obtained form the low resolution images is different from the MTF of the blured high resolution images. (4)In order to improve the registration accuracy of Level 1 TLS Images,This paper proposes a new optical flow registration method.This approach uses the Normalized Cross-Correlation registration algorithm before using Lucas-Kanade optical flow registration algorithm.(5)This paper present a new super-resolution model to handle the Level 1TLS images.In this model,we introduce the volatile blurs into the gaussian PSF model and take into account the errors of image registration.By Alternating Minimization(AM) algorithm,we can estimate the blur and HR image progressively.Experimental results are shown that our model correspond to the actual TLS images and the AM blind super-resolution approach can be used to enhance the resolution of aerial Images and remote sensing.(6)The MSSIM index to evaluate the result of super-resolution reconstruction is introduced.Based on the TLS images,this paper analyze the reconstruction result of all kind of superresolution algorithm.Experimental results are shown that the robust super-resolution algorithm is better than the other super-resolution algorithms and the MSSIM index is better than the other indexs

Related Dissertations

  1. Research on the Super-resolution Technologies of Polarimetric SAR Images,TN957.52
  2. Superresolution of Hyperspectral Images Based on Spatial-Spectral Information Coordination,TN911.73
  3. Research of Image Mosaic Technology,TP391.41
  4. Research on Visual Detection and Tracking of Mobile Robots,TP242.62
  5. Study on Image Registration and Image Matching of the Robot System for Substation Equipment Inspection,TP242.62
  6. Study on the Image Registeration Integrated with the LQ Model,R815
  7. A Preliminary Study on Bare Soil Extraction and Its Moisture Retrieval from High Resolution SAR Data,S152.7
  8. Research on Regression-based Super-Resolution Image Reconstruction Technique,TP391.41
  9. Medical image registration platform and combines new gray with geometric information Registration Measures,TP391.41
  10. Infrared and visible image registration and fusion research,TP391.41
  11. Feature points based spatial information distribution histogram matching method,TP391.41
  12. Image registration based on the rotation angle calculation methods sand,TP391.41
  13. Image Matching Based on Local Invariant Features,TP391.41
  14. Multi-spectral remote sensing image registration and fusion research,TP751
  15. The Study on Performance Appraisal of the Villages and Towns Government Based on the Performance Prism Theory,D625
  16. Some Research on Medical Image Registration and Fusion,TP391.41
  17. Study on Registration of SAR Image and Optical Image,TN957.52
  18. Research on Surface Deformation Detecting by D-InSAR,TN957.51
  19. Study on Three-Dimensional Stratum Visualization of Mining Subsidence,TP391.41
  20. On Pixel-level Image Registration and Fusion Based on Wavelet,TP391.41
  21. Research and Implementation of Moving Obstacle Detection Technology Based on Monocular Vision,TP391.41

CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
© 2012 www.DissertationTopic.Net  Mobile