Dissertation > Excellent graduate degree dissertation topics show

Ship Target ocean remote sensing images and Wake Detection

Author: LiHongKang
Tutor: WangJianGuo
School: University of Electronic Science and Technology
Course: Signal and Information Processing
Keywords: Remote Sensing Image Ship Target Detection Wake Detection Ship characteristic parameters
CLC: TP751
Type: Master's thesis
Year: 2008
Downloads: 324
Quote: 0
Read: Download Dissertation

Abstract


In recent years , the use of remote sensing images for ship detection and monitoring of research and technological development in the field of ocean remote sensing given high importance as remote sensing data is one of the most important marine applications . When the massive remote sensing image data for ship detection and surveillance , in order to timely and effective detection and extraction of ship target information , the need to carry out automatic detection algorithm . In this thesis, the application of remote sensing images of the ocean as a backdrop, the focus on remote sensing image ship target detection, ship wake detection, feature extraction and other aspects of marine research . Research papers , mainly in remote sensing image ship target , wake detection method and its application research. Firstly, studied the four common characteristics of wake generation mechanism , obtained by simulation of the sea , Kelvin wake, narrow V- wake, wake turbulence and internal wave wake characteristics . Allows us to understand the nature and understanding of the generation mechanism of different trails and spatial distribution patterns , in order to fully understand these types of wake model foundation. This paper analyzes the ship detection in remote sensing image research status ; experimental analysis is given by two-parameter CFAR algorithm , K- distributed CFAR algorithm and based on local window CFAR algorithm K- distribution characteristics and scope . In Ship Wake Detection algorithms , the paper summarizes the detection method of remote sensing image wake conventional structure , and highlights two categories detection methods, a class detection method is based on the geometric characteristics of the wake , and the other detection methods are based on the wake region and the entire remote sensing image background in statistical distribution differences. In the list of existing major ship wake detection method, for RADON, HOUGH other conventional algorithm , this paper proposes a new wake detection methods. Based on the theoretical analysis with simulation and real remote sensing images of the new detection methods were tested , and the test results are given analysis and evaluation . Finally, based on remote sensing images on the characteristics of the target ship , the ship's parameters studied characteristics of three types of parameters ( geometry , geography parameters , motion parameters ) features , and gives a quantitative parameter calculation method . In ship detection , wake detection and feature extraction studies , based on the characteristic parameters to achieve the estimated ship .

Related Dissertations

  1. Research on Remote Sensing Image Processing Combining High Fidelity Compression and Resolution Enhancement,TP751
  2. Road extraction algorithm based on region segmentation of remote sensing image,TP751
  3. Multi-spectral remote sensing image registration and fusion research,TP751
  4. Research and Implementation of K- means clustering of remote sensing images and watershed segmentation algorithm,TP751
  5. Soil Moisture Inversion Based on Remote Sensing Image,S127
  6. Based on Artificial Neural Network Classification of Remote Sensing Images,P237
  7. Remote Sensing Image Retrieval Based on Radiation and Spatial Information,TP751
  8. Research on Dodging Methods of Optical Remotely Sensed Image,TP751
  9. Research on Segmentation of UAV Remote Sensing Imagery and Ground Objects Extraction,TP751
  10. Research on Method of Retrieval from Remote Sensing Image with Global and Local Features,TP751
  11. Based on artificial immune system for remote sensing image retrieval algorithm,TP751
  12. Edge features based image retrieval technology for remote sensing,TP751
  13. Research on Methods for Texture Feature-based Retrieval of Remote Sensing Image,TP751
  14. Detection of Ship Wakes in SAR Images Based on Wavelet Transforms,TN957.52
  15. Research of SURF Based Remote Sensing Image Automatic Registration,TP751
  16. The Ephemeral Gully Geomorphic Features in Loess Plateau of Northern Shaanxi Province and the Study of Its Affection to Vegetation,S157
  17. Unsupervised multi-channel remote sensing image change detection methods,TP751
  18. Based on the water quality of Weihe River quantitative remote sensing research of semi-supervised learning,P333.6
  19. Data Mining for Forest Space Information Features from Remote Sensing Images,TP751
  20. Design and Implementation of Remote Sensing Image Classification Algorithms for Parallel Computing System,TP751
  21. Research Based on Image Segmentation of Single Digital Photo and Method of Extracting Factor Measured Tree,TP391.41

CLC: > Industrial Technology > Automation technology,computer technology > Remote sensing technology > Interpretation, identification and processing of remote sensing images > Image processing methods
© 2012 www.DissertationTopic.Net  Mobile