基于神经网络的遥感图像识别算法

随着遥感技术的发展，将会有更多不同时间、空间分辨率的遥感图像数据应用于各个领域的工程中，遥感图像的模式识别便成为当前遥感图像应用研究领域中一个很重要的研究方向。人工神经网络（Artificial Network Networks，ANN）是一种模仿动物神经网络行为特征，进行分布式并行信息处理的算法数学模型。这种网络依靠系统的复杂程度，通过调整内部大量节点之间相互连接的关系，从而达到处理信息的目的。基于神经网络的遥感图像识别是遥感图像处理领域这几年的研究重点。本文首先介绍了人工神经网络和模式识别算法的基本理论知识，然后利用人工神经网络在Matlab工具箱环境中进行高空间分辨率的遥感图像识别。

Sensing Image Recognition Algorithm Based on Neural Network

With the development of the remote sensing technology, more and more remote sensing image data which are different in the time and space frequency will be applied to various fields of engineering. The pattern recognition of remote sensing imagery is becoming a very important research direction in the remote sensing image processing areas. Artificial Neural Networks （ANN） is a neural network to imitate animal behavior,which is the distributed parallel processing algorithms mathematical model. This network relies on the complexity of the system, by adjusting the internal connection between a large number of nodes,in order to achieve the purpose of dealing with information. Remote sensing based on neural network image recognition is the focus of the remote sensing image processing research in these years. First of all,this thesis introduces the basic theory of artificial neural networks and the pattern recognition,and uses the artificial neural network toolbox in the Matlab environment for the high spatial resolution remote sensing image recognition.