The Research Of Web GIS And Map Compression

With the widely use of the internet and the fast growing of the customer's needs of GIS, GIS develops towards the network-orientation and intelligent-orientation direction. As a result, Web GIS comes into being. Web GIS is based on the Web platform. It is a spatial data managing system which provides various basic GIS functions, distributed calculating and spatial data managing for the application of the geography information science in the network environment. Essentially, it is a distributing spatial information managing and serving system with the ability of spatial data managing, distributed cooperation, web publishing and geography information application and so on. According to the diversity of the clients, there are two kinds of map services provided by the Web GIS server: vector map service and image map service. The map which is sent to the fat client is vector map and which is sent to the slim client is image map. The fat client needs to download some plug-ins in order to use the map service. Generally, the slim client is more convenient then the fat client, so slim client is more popular, however, the amount of the data to be transmitted is big in the slim client mode, so how to reduce the redundancy of the data is an important problem.This paper studied the various developing modes of Web GIS and the corresponding principles, and mainly studied the request and response processing of the image map service which is applied in the slim client mode. As the image compression algorithm SPIHT takes much time in the quantization when the compression rate goes down, it bears bad real-time ability, so this paper has made some research on the algorithm which can enhance the image compression speed, use the TCQ (Trellis Coding Quantization) algorithm to quantize the wavelet coefficients instead of the scalar quantity quantizing method, TCQ is the best kind of vector quantization, it uses the trellis to expand the signal space, so it can enhance the information that is denoted by each bit. It generates the code book according to the value of the coefficients which is to be quantized. Coding and decoding use the same algorithm to generate the code book, so the code book doesn't have to be transmitted. In this way the compression efficiency is quite high and the compression time is much less too. This algorithm will have a great meaning to the multiresolution transmission of the image map.