1) Remote sensing image segmentation
遥感图像分割
1.
Remote sensing image segmentation is not only the key implementation step for understanding remote sensing image but also a comprehensive study of the subject which across the image processing, pattern recognition, computer vision, neural network and other areas of multidisciplinary research.
遥感图像分割是实现遥感图像理解关键的一步,是一个跨越图像处理、模式识别、计算机视觉、神经网络等多学科研究领域的综合性研究课题,有着广阔的应用前景,近年来受到人们普遍重视。
2.
In response to these problems,by combining evolving clustering(ECM) with FCM algorithm,put forward a new method of remote sensing image segmentation.
针对上述问题,结合进化聚类(ECM)和FCM算法,提出了一种遥感图像分割的新方法。
2) high resolution image segmentation
高分辨遥感图像分割
4) remote sensing image classification
遥感图像分类
1.
Research on remote sensing image classification using Ant Colony Optimization(ACO) based classification rule mining algorithm;
基于蚁群优化分类规则挖掘的遥感图像分类研究
2.
Application of Support Vector Machine and Fuzzy Theory for Remote Sensing Image Classification;
支持向量机和模糊理论在遥感图像分类中的应用
3.
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。
6) Classification of the Remote Image
遥感图像的分类
补充资料：高光谱分辨率遥感图像及图像光谱信息提取
高光谱分辨率遥感图像及图像光谱信息提取
高光谱分辨率遥感图像及图像光谱信息提取 郑兰芬供稿
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条