Remote sensing image classification is an important research field of information processing.
遥感影像分类是遥感信息处理的重要研究领域之一。
Improving classification accuracy is always the focus for remote sensing image classification.
提高遥感图像分类精度一直是受到普遍关注的焦点问题。
Texture analysis has become an important means for improving the accuracy of remote sensing image classification.
纹理分析是提高遥感影像分类精度的重要手段之一。
Current remote sensing image classification models and algorithms commonly used statistical methods, neural networks, Bayesian and so on.
目前遥感影像分类的常用模型和算法有统计学方法、神经网络、贝叶斯等。
In this paper, we propose an automatic multispectral remote sensing image classification technique based on improved probabilistic diffusion.
为了提高遥感图像分类精度，提出了一种基于概率扩散模型的多光谱遥感图像自动分类技术。
Then, an experiment of remote sensing image classification is carried out to verify the authenticity based on the relations between samples and bands.
然后，在遥感影像分类实验中，借助样本数量与波段数目的关系，验证了理论分析的结果。
Smooth implementation of this project, for solving uncertain information in remote sensing image classification has a high theoretical value and a good prospect.
本项目的顺利开展，对于解决遥感影像中不确定信息分类问题具有较高的理论价值和良好的应用前景。
Absrtact: the main problem of remote sensing image classification is the contradiction of classification precision and algorithm complexity, and algorithm lacking of robust.
摘要：目前遥感图像分类算法面临的主要问题是分类精度与算法复杂度的矛盾及算法缺乏鲁棒性。
The main drawback of traditional remote sensing image classification methods is its low precision. A neural network-based remote sensing image classification technique has been presented.
针对传统的遥感图像分类方法分类精度低的缺点，提出了一种基于神经网络的分类方法。
The supervised learning algorithm was usually used for remote sensing image classification, but its training samples need to be chosen by manual, which was boring and sometimes even difficult.
遥感图像分类方法通常采用监督的学习算法，它需要人工选取训练样本，比较繁琐，而且有时很难得到；而非监督学习算法的分类精度通常很难令人满意。
Remote sensing image classification is an important means for quantified remote sensing image analysis, and remote sensing image fusion can effectively improve the accuracy of image classification.
遥感影像分类是遥感定量化分析的重要手段，遥感影像融合是提高分类正确率的有效途径之一。
Thus, some scholars use object-oriented information extraction technology to classify the remote sensing image, greatly increased the accuracy of high-resolution remote sensing image classification.
于是，有些学者将面向对象信息提取技术运用到遥感影像的分类中，大大提高了高分辨率遥感影像的分类精度。
The point is about introduction of Highlighted in remote sensing image process used radiation to enhance remote sensing image, computer classification process technology.
着重介绍了在进行遥感影像处理过程中所用到遥感影像辐射增强、计算机分类等的处理技术。
In this paper, fuzzy sets theory was applied in classification of remote sensing image, classification of remote sensing image was researched.
本文将模糊集理论应用于遥感图像的分类中，研究了模糊集理论在遥感图像分类中的应用。
The classification of Remote Sensing Image is an important measure for obtaining information of remote sensing image.
对遥感图像分类是遥感图像信息获取的重要手段。
Remote sensing classification is the main method of the analysis of remote sensing data and very important research content in remote sensing image procession.
遥感分类是主要的遥感数据分析方法，是遥感图像处理中的一个非常重要研究内容。
The statistic classification method, which is the basis of various new classification methods, is very popular in the classification of remote sensing image.
统计分类方法在遥感图像分类中运用得很普遍，同时统计分类方法还是各种新兴分类方法的基础。
Furthermore this algorithm has no influence on such applications as edge detection and image classification of the disguised remote sensing image which has hidden the secrete information.
此外，该算法对隐藏了机密信息后的伪遥感影像的各种应用，如边缘检测和影像分类等均没有影响。
This paper puts forward a new method of invariant texture classification for remote sensing image.
本文提出了一种遥感图像旋转不变纹理分类的新方法。
In remote sensing image processing, image classification plays the role of feature's extraction.
在遥感图像的处理中，图像分类起到特征提取的作用。
Study the object-oriented classification technology of high resolution remote sensing image.
研究了面向对象高分辨遥感图像分类技术。
The system can be also used to class and recognize soil pattern from remote sensing image, and to examine and evaluate the classification precision.
该系统可以对遥感图像进行土壤类型的分类识别，并对分类精度进行监测与评价。
The spatial information of the image and evidence theory is applied to classification of remote sensing image based on neural networks.
把影像的空间信息融入分类决策，提出了一种基于证据理论与神经网络的遥感影像分类方法。
The hyperspectral remote sensing image is rich in spectrum information, so it can be better to carry on the ground targets classification.
高光谱遥感影像具有丰富的光谱信息，在地物分类识别方面具有明显的优势。
In this paper the relaxation algorithms and their applications in image matching, edge extraction and remote sensing imagery classification are described.
本文阐述了松弛法算法及其在图象匹配、边缘抽取及遥感图象分类等方面的应用。
BP neural network is widely used for classification of remote sensing image data nowadays.
BP神经网络近年来广泛地应用于遥感影像分类中。
A new automatic classification model of remote sensing image using pixel information decomposition combined with neural network classification is proposed in this paper.
提出了一种新的基于像元信息分解和神经网络分类相结合的城市绿地遥感信息自动提取方法。
Futhermore, it also includes the improvement of current grassland classification and the level of interpretation by means of remote sensing image.
同时对改进现行草地分类、提高遥感图象解译水平等问题进行了讨论。
Futhermore, it also includes the improvement of current grassland classification and the level of interpretation by means of remote sensing image.
同时对改进现行草地分类、提高遥感图象解译水平等问题进行了讨论。
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