Development of Analysis Processing System Using Orbital Satellite Image Data

对轨道卫星被动传感器图像数据处理系统进行了改进和改造。这个创新的IBASYS系统的内容描述如下：(1)将原来的FORTRAN程序翻译成c++，使其可以在工作站和个人计算机上运行。(2)为了验证分析准备所需的数据条件，将彩色图案从7个波段扩展到18个波段。(3)为了提高图像几何变换的处理效率，分层增加了误差分析的人机处理和图像变换处理。(4)在无监督分类中加入K-means方法，开发了一种采用栅格分类处理的算法。(5)增加了一种通用概念算法来验证选定的训练数据在图像数据上的应用。(6)作为分类方法的扩展，对模糊理论与神经网络理论相结合的模糊神经网络分类方法进行了理论研究，使轨道卫星图像数据分类成为可能。

The SAIAS system that processes image data extracted from passive sensors onboard in orbital satellites is improved and renovated. The contents of this innovated IBASYS system is described below :(1) The original FORTRAN programs are translated to C++, making possible to run on workstations and personal computers.(2) To verify the data conditions necessary for analysis preparation, the color pattern is expanded from 7 to 18 bands.(3) To improve the processing efficiency of geometric transformation of an image, the man-machine processing of error analysis and the image transformation processing was hierarchically added.(4) The K-means method is added in the unsupervised classifications, developing an algorithm using a raster classification processing.(5) A general notion algorithm to verify the application of a selected training data on an image data is added.(6) As an expansion to the classification methods, a theoretical investigation is made on FNN classification, a combination of fuzzy theory and neural network theory, and is made possible to classify an orbital satellite image data.