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classification is Ok for the image segmentation.
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图像的非监督分类，主要包括K均值、FCM等-Unsupervised classification of images, including K-means, FCM
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图像的监督分类，并给出了数字识别等具体实例-Supervision of the image classification, and gives specific examples such as digital identification
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基于matlab神经网络的遥感图像分类，使用了BP神经网络-Matlab neural network-based remote sensing image classification using BP neural network
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基于图像检索的matlab代码，基于内容的图像检索中的一些关键环节：特征提取：颜色直方图；纹理特征等 相似度：马氏距离，欧氏距离等 相关反馈：机器学习方法，如SVM，神经网络等 检索与分类：两个很相似的样本距离很小，虽然两个不相似的样本距离未必很大-content-based image retrieval of some of the key issues : Feature Extraction : color histogram Texture characteristics of si
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图像分割，形态学处理，特征提取，识别分类-Image segmentation, morphological processing, feature extraction, recognition classification
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基于VC6.0的MFC实现，功能包括：图像分类（K均值、ISODATA）、图像融合（基于高通滤波的加权融合和非加权融合、HIS融合）、直方图均衡化、直方图匹配、RGB与HIS之间的相互转换-based on MFC, functionality include: image classification(K means and ISODATA),image fusion(fusion based on HIS transformation and fusion based on high pas
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K均值算法和ISODATA算法的源码，用C++编写，内附一张TM的卫星影像作为实验数据，具体算法原理可以参考武大舒宁、马洪超、孙和利版的《模式识别》一书-The source code of K Means and ISODATA algorithm, written in C++, with a TM image attached. For concrete algorithm, you are referred to the book Pattern Recognition written
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基于压缩感知的纹理图像分类，介绍了一种新的高效算法：分类压缩感知。与一般压缩感知及其他方法在四大纹理数据库上对比。有原文献及自己的译文-Introduced a new efficient algorithm based on compressed sensing texture image classification, compressed sensing: Category. Original literature and translation
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对遥感影像进行增强，平滑去噪等，还包括K均值分类-Remote sensing image enhancement, denoising, also including the K-means classification
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用C++语言编写的MFC程序，用K均值和ISODATA算法实现BMP影像的自动分类。提供良好的交互接口，用户可在图像上选择初始聚类中心和设定分类相关参数。适合作为初学者学习分类算法和MFC编程的参考资料。提供了文档说明程序的操作过程。-MFC program with C++ language, K-means and ISODATA algorithm to achieve the automatic classification of BMP images. Provide a good i
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主要从遥感图像监督分类过程、ERDAS+IMAGINE+应用手册、计算分类以及最后对遥感图像处理中分类的探讨论述各个过程，蛮好的资料。-Mainly from the remote sensing image classification process, ERDAS+IMAGINE+ application manual calculation, classification and the processing of remote sensing image classification d
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数字图像处理模式识别分类Visual C++源代码-Digital image processing pattern recognition classifier Visual C++ source code
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提供了三类场景“bedroom”、“CALsuburb”、“industrial”的样本特征集以及原始图像，分别用线性分类器、树状分类器、SVM分类器以及AdaBoost分类器对其进行区分。其中AdaBoost分类器有部分内容调用了Vezhnevets Alexander编写的源码-Provides three types of scenes " bedroom" , " CALsuburb" , " industrial" sample fea
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将常见的图像配准方法分为基于图像灰度的方法和基于图
像特征的方法两大类。 以此为分类基础， 对国内外现有的图像配准技术和方法进行了分析和评述，
并重点介绍了基于图像特征的配准方法。-The common method for image registration based on image gray into the methods and methods based on image features two categories. As a classification based
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BP神经网络图像分类程序,代码很好懂，适合初学者。样本选的不是很大。-BP neural network image classification procedures, code easy to understand for beginners. Sample selected is not great.
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Matlab写的SVM图像分类程序，是完整的可运行的图像分类程序，高手可以研究一下。-Matlab write SVM image classification procedure is complete working image classification procedures, experts can look at.
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digital image watermarking using different approach review
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本文实现了09年CVPR的文章Linear Spatial Pyramid Matching using Sparse Coding for Image Classification-This package contains the Matlab codes implementing the ScSPM algorithm described in CVPR 09 paper
"Linear Spatial Pyramid Matching using Sparse Coding for
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texture based image analysis
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