| Abstract | 第1-8页 |
| 1.Introduction | 第8-13页 |
| ·Foreword | 第8页 |
| ·Background of the acoustic vision research | 第8-9页 |
| ·Development of sonar image generation and processing | 第9-11页 |
| ·Purpose and significant contents of this thesis | 第11-13页 |
| 2.Sonar image generating principles | 第13-24页 |
| ·Foreword | 第13页 |
| ·Principles of sonar and sonar equation | 第13-16页 |
| ·Theoretical background of sonar imaging | 第16-19页 |
| ·One approaches to generate image:Beamforming | 第19-24页 |
| 3.Sonar image preprocessing | 第24-27页 |
| ·Foreword | 第24页 |
| ·Image enhancement by reducing the speckle noise | 第24-27页 |
| 4.Image segmentation | 第27-39页 |
| ·Foreword | 第27-28页 |
| ·The main approaches to segmentation of sonar image | 第28-30页 |
| ·Sonar Image Segmentation Based on Markov Gauss-Rayleigh Mixture Model | 第30-39页 |
| ·D classification of the seafloor based on sonar images | 第39-51页 |
| ·Foreword | 第39页 |
| ·Summary of the main approaches to classify the seafloor | 第39-40页 |
| ·Analysis of the problems in the sonar image generation | 第40-42页 |
| ·Seafloor classification using Gabor filter | 第42-51页 |
| 6.Two more efficient classification algorithms of sonar images | 第51-64页 |
| ·Foreword | 第51页 |
| ·Sonar images classification based on the information fusion methods | 第51-57页 |
| ·Another efficient classification algorithm of seafloor using Gabor Wavelet | 第57-62页 |
| ·Conclusion | 第62-64页 |
| 7.Conclusion and Future work | 第64-66页 |
| ·Conclusion | 第64页 |
| ·Future work | 第64-66页 |
| Acknowledgement | 第66-67页 |
| Main Work Achievement of the author | 第67-68页 |
| References | 第68-70页 |
