Please read your package and describe it at least 40 bytes. System will automatically delete the directory of debug and release, so please do not put files on these two directory.
標簽： automatically describe package Please
上傳時間： 2017-03-28
上傳用戶：372825274
lease read your package and describe it at least 40 bytes. System will automatically delete the directory of debug and release, so please do not put files on these two directory
標簽： automatically describe package System
上傳時間： 2013-12-02
上傳用戶：moerwang
lease read your package and describe it at least 40 bytes. System will automatically delete the directory of debug and release, so please do not put files on these two directory
標簽： automatically describe package System
上傳時間： 2013-12-13
上傳用戶：qlpqlq
lease read your package and describe it at least 40 bytes. System will automatically delete the directory of debug and release, so please do not put files on these two directory
標簽： automatically describe package System
上傳時間： 2017-03-28
上傳用戶：baiom
lease read your package and describe it at least 40 bytes. System will automatically delete the directory of debug and release, so please do not put files on these two directory
標簽： automatically describe package System
上傳時間： 2014-02-28
上傳用戶：dongbaobao
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.
標簽： present modalities existence different
上傳時間： 2017-04-03
上傳用戶：qunquan
-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. Mutual Information is the similarity measure used in this case for optimizing the two images. This method requires estimating joint histogram of the two images. The fusion of images is the process of combining two or more images into a single image retaining important features from each. The Discrete Wavelet Transform (DWT) has become an attractive tool for fusing multimodal images. In this work it has been used to segment the features of the input images to produce a region map. Features of each region are calculated and a region based approach is used to fuse the images in the wavelet domain.
標簽： present modalities existence different
上傳時間： 2014-03-04
上傳用戶：15736969615
The double-density DWT is an improvement upon the critically sampled DWT with important additional properties: (1) It employs one scaling function and two distinct wavelets, which are designed to be offset from one another by one half, (2) The double-density DWT is overcomplete by a factor of two, and (3) It is nearly shift-invariant. In two dimensions, this transform outperforms the standard DWT in terms of denoising however, there is room for improvement because not all of the wavelets are directional. That is, although the double-density DWT utilizes more wavelets, some lack a dominant spatial orientation, which prevents them from being able to isolate those directions.
標簽： double-density improvement additional critically
上傳時間： 2017-04-03
上傳用戶：dongbaobao
In computer vision, sets of data acquired by sampling the same scene or object at different times, or from different perspectives, will be in different coordinate systems. Image registration is the process of transforming the different sets of data into one coordinate system. Registration is necessary in order to be able to compare or integrate the data obtained from different measurements. Image registration is the process of transforming the different sets of data into one coordinate system. To be precise it involves finding transformations that relate spatial information conveyed in one image to that in another or in physical space. Image registration is performed on a series of at least two images, where one of these images is the reference image to which all the others will be registered. The other images are referred to as target images.
標簽： different computer acquired sampling
上傳時間： 2013-12-28
上傳用戶：來茴
Real-Time Design Patterns: Robust Scalable Architecture for Real-Time Systems. In this book, Bruce Douglass illustrates for the first time how two important contemporary software engineering advances鈥攑atterns and the UML鈥攃an be applied advantageously to the concepts and techniques traditionally used in mainstream real-time software.
標簽： Real-Time Architecture Patterns Scalable
上傳時間： 2013-12-13
上傳用戶：6546544
