A new feature level fusion and moving target tracking method for IR and visible images is proposed.
提出了一种红外与可见光图像的新颖的特征级融合与运动目标跟踪方法。
Image fusion can be divided into three levels, pixel level fusion, feature level fusion and the decision-making level fusion.
图像融合可以分为三个层次：像素级融合、特征级融合和决策级融合。
Next the general method of applying fuzzy ARTMAP model to feature level fusion is also expounded and we put forward a learning algorithm with adaptive vigilance parameters for each cluster.
继而研究了模糊artmap网络用于特征层融合识别的方法，并提出了一种网络警戒参数自适应调整新算法。
There are many experts and scholars, have researched the image fusion methods. Generally. it can be fused at three levels: pixel level fusion, feature level fusion and decision level fusion.
已有很多专家学者对影像融合方法做过研究，一般可在三个层次上进行融合，即像素级融合、特征级融合以及决策级融合。
A new feature level fusion method of target's contour was proposed, which minimizes norm's square of the difference of control point vectors of convergent dynamic contours in two modal images.
提出了一种新的目标轮廓特征级融合方法，求解两类模式图像的收敛动态轮廓线控制点向量差的范数平方极小化。
The fault diagnosis system is classed into data fusion level module, feature level module and decision fusion level module according data fusion method.
将故障诊断系统按数据融合的方法分为数据级融合模块、特征级融合模块和决策级融合模块。
The feature level module adopts RBF neural network to extract feature of data and to make feature fusion.
特征级融合模块采用RBF神经网络，其功能是提取数据特征进而特征信息融合。
According to the fusion levels, there are data level, feature level, decision level included in data fusion.
从融合的层次结构出发，数据融合技术可分为数据级、特征级和决策级三个融合层次。
From the abstract level, image fusion can be divided into: pixels-level fusion, feature-level fusion and decision-level fusion.
图像融合从抽象层次上可分为：像素级融合、特征级融合和决策级融合。
Regarding this, a novel feature level approach to image fusion is proposed based on discrete dyadic wavelet transform for multi-scale image edge detection.
本文提出了一种基于离散二进小波变换的多尺度边缘检测和图像融合的方法，实现了特征级图像融合。
One of the keystones of the paper is image fusion algorithm based on pixel level and feature level.
本文研究的一个重点是像素级和特征级的图像融合算法。
The research in this paper is executed mainly at pixie level and feature level image fusion.
图像融合分为三个层次：像素层、特征层和决策层。
The data fusion level module mainly handles the metrical data of multi-sensors and extracts the feature of faults.
数据级融合模块主要对多传感器的测量信号进行处理，提取出故障诊断的特征信息。
The image fusion can be divided into three fusion level, namely: pixel, feature and decision levels.
图像融合一般可分为像素级、特征级和决策级图像融合。
The decision fusion level module USES D-S evidence theory to fuse the local diagnostic results of feature fusion level, then get the final diagnostic results.
决策级采用D - S证据理论的方法对特征级局部诊断的结果加以融合，得到最终的诊断结果。
In this dissertation, three levels of image fusion technology: pixel-level, feature-level and decision-level are studied, and some novel methods of analysis and processing are presented.
论文从像元、特征和决策融合三个方面研究了多源图像融合技术，提出了一些新的分析处理方法。
From the abstract level of the data which is to be dealed with, the image fusion technique can be divided intoto pixel level, feature level and decision level.
从待处理数据的抽象层次上分，融合技术可分为像素级、特征级和决策级三种。
Using the strategy of feature-level fusion and decision-level fusion against the fusion of hands characteristics and expression characteristics, and analyzing the experimental results.
分别采用特征层融合和决策层融合的策略对手部特征与表情特征进行融合，并对实验结果进行了分析。
Under different classifications, image fusion algorithms can consist of space domain and transform domain, or pixel-level, feature-level and decision-making level.
根据图像融合分类的不同，图像融合的算法可分为空域、变换域融合算法，或像素级、特征级和决策级融合算法。
We study the algorithms of feature-level fusion based on the viewpoint of dependence and independence multi-variant data analysis, respectively.
首先从多元数据分析的角度，研究了基于相关性的多元数据分析和基于独立性的多元数据分析的特征融合方法。
This paper surveys pixel, feature, and symbol level image fusion methods and compares the characteristics of different fusion levels. A few image fusion algorithms of each level are presented, p…
本文讨论了图像融合各层次的融合算法以及红外图像、可见光图像、多谱图像、雷达图像等的融合问题。
This paper surveys pixel, feature, and symbol level image fusion methods and compares the characteristics of different fusion levels. A few image fusion algorithms of each level are presented, p…
本文讨论了图像融合各层次的融合算法以及红外图像、可见光图像、多谱图像、雷达图像等的融合问题。
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