Research On Key Technologies Of Modeling And Visualization For The Marine Environment Data Field

With the development of the world, the ocean plays an increasingly significant strategic role in the field of politics, economy, military and so forth. As a result, exploration and research of the ocean has showed a vigorous developing trend. The one who grasps the objective laws of the ocean, who makes full use of Marine resources will gain an advantage in dominating the opportunities of development. As we all know, accurate and profound analysis of ocean data is a precondition for effective marine exploration and utilization. Therefore, it's the foundation of full understanding and utilizing the sea to establish a highly efficient model for the Marine environment data, which is in accordance with the characteristics of ocean. At the same time, visualization of the Marine environment data, which makes abstract data more concrete and intuitive, is of equal importance. That is because it will help people understand the nature and connotation of the sea more easily and profoundly.This paper focuses on the following three aspects: the Marine environment data modeling, vector field data interpolation and vector field visualization. The main work of the paper is as follows:(1) In the aspect of data modeling, this paper analyzes the basic elements of the Marine environment and the characteristics of Marine data. A two-dimensional ground state modified model for the Marine environment is proposed, against the deficiency of the ground state models in existence. First of all, divide the Marine environmental elements cycle by significant phases. Second, combine data from a number of significant phases in one period to make the base state axis. Update the data from the same significant phase to form different file axis.(2) In terms of vector field interpolation, a novel vector field data interpolation algorithm based on Lagrange fluid particle motion model is presented by studying the characteristics of fluid motion. It first chooses six sampling points which are nearest to the interpolation point and estimates the locations they reach at the next moment based on their vector data and position coordinates. Then, the algorithm makes use of the location coordinates of the present moment and next moment to calculate the undetermined coefficients of the system equations of fluid motion. After that, the coordinate of any point can be determined based on the system equations. It means that we can deduce the vector data of any point by its coordinate easily.(3) In terms of vector field visualization, we find that classic line integral convolution and its improved algorithm have some shortcomings in expression of vector field strength through analysis. In order to resolve the shortage and seek a more effective way, this paper investigates a texture visualization algorithm based on field drive. The algorithm first combines vector field intensity and the input noise texture to generate the in-put noise texture driven by field strength. Then, get the gray output texture through line integral convolution technique. Finally, the color output texture image is obtained by pseudocolor enhancing technology. The acquired color texture can not only show the direction of the vector field, but also reflect the size of the vector.