Research Of Visualization Algorithm Of Underwater Acoustic Data

The visualization of volume data is a branch of visualization of cientific computing. It is a technology that using the two-dimensional images which human visual can sense to show the internal characteristic information of three-dimensional data. At present, this technology widely used in medical research, weather forecast, geological exploration, ocean exploration, etc. In the visualization of hydroacoustics field, it makes use of this technology of 3-d visualization constructing a three-dimensional image of the underwater acoustic data. And it effectively expresses the volume data by means of image displaying. That makes researchers analyze underwater target more convenient. The development of visualization technology makes human beings better know the ocean and ocean detection has new breakthrough. The classification of volume data and rending of volume data as two important steps in visualization process, is a research hotspot in the field of visualization. In this thesis, by the analysis of the characteristics of underwater acoustic data, and considering the shortages of the current algorithms respectively in classification or rending, corresponding algorithms for 3-d reconstruction of underwater acoustic data are proposed. In this thesis, the main research directions and and innovation points are as follows:1?This thesis briefly introduces the research background and the research status of visualization of acoustic data. Detailed introduces the technology theory of acoustic data that are used in this thesis. It summarizes the current research methods of three-dimensional reconstruction, and analyses the problems of the current research methods existing in the process of implementation. In order to solve the problems in interpolation algorithms of 3-d visualization, a method of using the inverse distance weight (Inverse Distance Weight, IDW) interpolation for volume data is proposed through the analysis of the characteristics of underwater acoustic data. Inverse distance weight interpolation algorithm is a relatively fast and simple interpolation method. It gets the value in the sample point by choosing appropriate interpolation parameters. And finally finishes interpolation calculation of underwater acoustic data. Experimental results show that the proposed method in this thesis can achieve good effect in interpolation of underwater acoustic data and have clear and better rending result of suspected target.2?Because of the uncertainty of underwater acoustic data and the gray overlap between various substances, classification of the data is more complicated. And the rending effects are not ideal. In this thesis, a method of classification of underwater acoustic data based on the conditional entropy of histogram is proposed. Let the maximum values which come from the largest eigenvalue of each section histogram as a condition. Then using the discriminant of conditional entropy of subsection histogram, a threshold is calculated for each section. Finally the classification of underwater acoustic data is completed. Experimental results show that the proposed method in this thesis can solve the problems well and also achieve good effect in classification of underwater acoustic data and have clear and better rending result of suspected target.