城市街区用地类型的普查自动化多年以来一直是遥感模式识别的重点研究目标。
The destination of this thesis is to improve the pattern recognition algorithm for the classification to the land-use of urban blocks on remote-sensing images.
遥感图像目标自动识别技术是计算机模式识别与图像处理领域非常活跃的研究课题。
The technology of object automatic recognition on remote-sensing image is a very active research field in pattern recognition and image processing these years.
试验表明，应用电子计算机对遥感数据进行森林模式识别分类是可行的，方法灵活多样，而且精度可以保证。
It has been shown that it is feasible to classify the forest model identification by processing the remote sensing data with computer, which has high accuracy.
图像配准是图像处理的一个基础问题，它广泛应用于计算机视觉、模式识别、医学图像分析、遥感数据分析等领域。
Image registration is a foundation problem in image processing. It is widely used in computer vision, pattern recognition, medical image analysis and remote sensing image analysis.
遥感图像的自动识别是遥感、计算机视觉和模式识别等领域面临的重大挑战。
Automatic recognition of remote sensing image is a great challenge in the field such as remote sensing, computer vision, pattern recognition and so on.
传统统计模式识别方法进行遥感影像分类时要求数据服从正态分布且难以加入地理辅助数据。
The traditional statistical classifier is suitable in making RS image classification in normal distribution and unsuitable in doing with the data in discrete distribution, such as the geographic data.
传统统计模式识别方法进行遥感影像分类时要求数据服从正态分布且难以加入地理辅助数据。
The traditional statistical classifier is suitable in making RS image classification in normal distribution and unsuitable in doing with the data in discrete distribution, such as the geographic data.
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