1)image registration图像配准
1.Study on local extremum of object function in mutual information-based image registration;基于互信息图像配准中的局部极值问题研究
2.Mono-modality image registration based on modified mutual information;基于互信息的同模态医学图像配准
3.Research on CT image registration algorithm and its implementation;CT图像配准算法的研究与实现
英文短句/例句
1.Image Registration and Fusion Technology in the Detection of Double Spectrum Image Detection;双光谱图像检测的图像配准融合技术
2.Color Image Registration Model Based on Abstract Matching Flow基于抽象匹配流的彩色图像配准模型
3.Application of Image Registration in Photographic Superimposition图像配准技术在颅像重合中的应用
4.The Application Research on Imaging Registration for Medical Images Processing;图像配准技术在医学图像处理中的应用研究
5.Deterministic Perturbation PV Interpolation in Image Registration图像配准中确定性扰动PV插值算法
6.Medical Image Registration Based on Quantitative-Qualitative Measure of Mutual Information;基于定量定性互信息的医学图像配准
7.Remote Sensing Image Registration Based on Multi-Features;基于多特征遥感图像配准方法的研究
8.Study on Registration and Fusion Multimodality Medical Image;多模态医学图像配准和融合技术研究
9.The SIFT Research and Implementation Based on the Image Registration;基于图像配准的SIFT算法研究与实现
10.Research on Image Registration Based on Support Vector Machines;支持向量机在图像配准中的应用研究
11.Medical Image Registration Based on Normal Vector Information;基于法向量信息的医学图像配准研究
12.Study on Image Registration in Multibaseline SAR-GMTI;多通道SAR-GMTI中的图像配准研究
13.A Research on the Algorithms of Registration and Fusion for Multi-spectral SAR Images;多波段SAR图像配准及融合算法研究
14.Research on Medical Image Registration Methods Based on Mutual Information;基于互信息的医学图像配准方法研究
15.Research and Application on Multimodality Medical Image Registration Algorithm;多模医学图像配准算法的研究与应用
16.Research on Algorithms for Medical Image Rigistration Based on Mutual Information;基于互信息的医学图像配准算法研究
17.Image Registration Based on Mutual Information;基于最大互信息的分层图像配准方法
18.Mutual Information Registration between Portal and Reference Images in Radiotherapy;放射治疗中射野图像与参考图像的互信息配准
相关短句/例句
image matching图像配准
1.In order to improve the stability and reliability of image matching,application of the scale invariant feature transform(SIFT) algorithm to image matching was studied.为了提高图像配准的稳定性和可靠性,研究了尺度不变特征变换(Scale Invariant Feature Transform)算法在图像配准中的应用。
2.The need of the image matching mode in the anti-shore engagement was expatiated on, and the shooting process was explained.阐述了对岸射击采用图像配准方式的必要性,说明了该射击方式的过程,并对图像配准方式射击进行了误差分析,给出了基于蒙特卡罗法的误差计算模型,并进行了仿真,指出了模型中存在的问题以及需要做的改进。
3.The image matching was realized by output buffer technology,the gray non-uniformity of mosaic chips was corrected by ratio average method.对多片TDI-CCD拼接技术以及由此带来的图像错位与像元不均匀性进行了介绍,采用输出缓存技术实现拼接TDI-CCD奇偶片输出图像配准,应用比值平均法校正拼接片间的灰度不均匀性,实现实时大视场拼接校正。
3)registration[英][,red??'stre??n][美]['r?d??'stre??n]图像配准
1.A new approach that incorporates hypercomplex correlation with robustness is presented for color image registration.为解决实际应用中彩色图像配准问题,针对已有的超复数互相关方法没有办法处理存在粗差的情况,在超复数互相关方法的基础上,结合鲁棒核函数,提出了一种超复数鲁棒相关的方法。
2.The thesis raises a new method of images registration on the basis of OCD-ICP.提出了一种基于OCD-ICP(OptimizeCornerDetection-IterativeClosetsPoint,优化角点集提取——迭代最近点)的图像配准方法。
3.The Study of Depth Map Registration Based on Laser Scanning;然后重点分析各种理论和技术的优缺点,并通过各类算法的归纳总结和集中经典算法的实验比较理解深度图像配准的实质和关键问题,提出了一种基于ICP的能达到一定速度和精确度的改进配准算法。
4)image co-registration图像配准
1.Tomography image co-registration algorithm based on principle of mechanics decomposition;基于力学分解原理的断层图像配准算法
2.Study on image co-registration based on matrix similarity degree;基于矩阵相似度的InSAR图像配准方法研究
5)complex image registration复图像配准
1.Based on the system model of interferomatric SAR and the statistics of interferometric phase error, the relationships between registration accuracy and the interferometric phase error are analyzed, and a practically accurate complex image registration method that meets the interferometric phase accuracy requirement is proposed.基于干涉合成孔径雷达 (Interfermetric Synthetic Aperture Radar-In SAR)的系统模型、干涉相位误差的统计特性 ,分析 In SAR配准精度与干涉相位误差之间的确定关系 ,讨论复图像配准过程中存在的问题 ,给出实用的 In SAR复图像配准方法 。
6)SAR image registrationSAR图像配准
延伸阅读
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
