Description: 采用共信息(mutual information)实现了图像对齐的功能（image registration）。这在数据融合，图像处理里是很重要的。-adopt information (mutual information) to achieve alignment of the image features (i MAGE registration). This data integration, image processing, was very important. Platform: |
Size: 186368 |
Author:sea |
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Description: 基于mutual information的图象配准程序-based on mutual information of the image registration procedures Platform: |
Size: 2048 |
Author:dylan |
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Description: 互信息图像配准，采用matlab实现，主要用于多模医学图像-mutual information image registration using Matlab to achieve, mainly for the Multi-Modal Medical Image Platform: |
Size: 57344 |
Author:hyx |
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Description: 这个源码是基于互信息图像配准用matlab的实现,需要的就下，啥也不说了-this source is based on mutual information image registration with the realization of Matlab, on the basis of need, not that the hero Platform: |
Size: 2048 |
Author:罗汉 |
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Description: 基于互信息的图像配准程序。用matlab编写的。有助于理解互信息。-based on mutual information of image registration procedures. Prepared using Matlab. Contribute to the mutual understanding of the information. Platform: |
Size: 3072 |
Author:周萍 |
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Description: 医学影像配准（Medical Image Registration）的入门资料。其中包括：
Fast Parametric Elastic Image Registration.pdf
Image Registration of Sectioned Brains.pdf
Mutual-information-based registration of medical images - a survey.pdf
Registration of histological serial sectionings.pdf
RegistrationMethodsOverview.pdf-Medical Image Registration (Medical Image Registration) introductory information. These include: Fast Parametric Elastic Image Registration.pdfImage Registration of Sectioned Brains.pdfMutual-information-based registration of medical images- a survey.pdfRegistration of histological serial sectionings.pdfRegistrationMethodsOverview.pdf Platform: |
Size: 11051008 |
Author:ricky yan |
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Description: 电子文档，基于互信息的图像配准，配准的文献为局部互信息，还有香农信息论文献-Electronic documents, based on mutual information image registration, registration of documents for the partial mutual information, as well as the Shannon information theory literature Platform: |
Size: 524288 |
Author:weajan |
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Description: 关于互信息图像配准方面的两篇权威的综述，对了解互信息配准方法有很大帮助，十分全面-On mutual information image registration aspects of two authoritative overview of the understanding of mutual information registration method are very helpful, very comprehensive Platform: |
Size: 1451008 |
Author:张旭 |
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Description: 使用图像的互信息进行自动图像配准源代码，这个程序通过归一化后的图像互信息进行图像的自动配准。中间通过旋转等进行图像对齐。-The use of images for automatic mutual information image registration source code, the procedure adopted by the normalized mutual information image after image of the automatic registration. Through the rotation between image alignment. Platform: |
Size: 74752 |
Author:yy |
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Description: 使用互信息进行2D图像自动配准源代码,应用平均互信息-The use of mutual information for automatic registration 2D image source code, the application of the average mutual information Platform: |
Size: 231424 |
Author:fh |
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Description: 基于最大互信息的图像配准算法源程序
用matlab编写的-Based on the maximum mutual information image registration algorithm using matlab source prepared Platform: |
Size: 580608 |
Author:wangdenuan |
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Description: The existence of numerous imaging modalities makes it possible to present different data present in different modalities together thus forming multimodal images. Component images forming multimodal images should be aligned, or registered so that all the data, coming from the different modalities, are displayed in proper locations. The term image registration is most commonly used to denote the process of alignment of images , that is of transforming them to the common coordinate system. This is done by optimizing a similarity measure between the two images. A widely used measure is Mutual Information (MI). This method requires estimating joint histogram of the two images. Experiments are presented that demonstrate the approach. The technique is intensity-based rather than feature-based. As a comparative assessment the performance based on normalized mutual information and cross correlation as metric have also been presented.-The existence of numerous imaging modalities makes it possible to present different data present in different modalities together thus forming multimodal images. Component images forming multimodal images should be aligned, or registered so that all the data, coming from the different modalities, are displayed in proper locations. The term image registration is most commonly used to denote the process of alignment of images , that is of transforming them to the common coordinate system. This is done by optimizing a similarity measure between the two images. A widely used measure is Mutual Information (MI). This method requires estimating joint histogram of the two images. Experiments are presented that demonstrate the approach. The technique is intensity-based rather than feature-based. As a comparative assessment the performance based on normalized mutual information and cross correlation as metric have also been presented. Platform: |
Size: 98304 |
Author:Harry |
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Description: 基于互信息的图像配准源代码，采用粒子群优化算法-Based on Mutual Information Image Registration source code, the use of particle swarm optimization algorithm Platform: |
Size: 497664 |
Author:hyliu |
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Description: 本人的计算机硕士论文，Powell和SA混合优化的互信息图像配准，-I am a computer master' s thesis, Powell, and SA Hybrid Optimization of mutual information image registration, Platform: |
Size: 90112 |
Author:tangyu |
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Description: 基于互信息的图像配准，使用pso和powell优化算法，GUI界面，proj.m-Based on mutual information image registration, use the pso and powell optimization, GUI interfaces, proj.m Platform: |
Size: 21504 |
Author:周一一 |
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Description: 图像配准中的两幅图像的归一化互信息计算方法代码-Image registration of two images of the normalized mutual information method code Platform: |
Size: 217088 |
Author:王丽 |
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Search - Mutual Information image registration