共查询到19条相似文献,搜索用时 125 毫秒
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为了提高无人机低空飞行时自主测速能力,本文提出了一种基于光电图像特征的无人机自主测速方法,首先利用光电设备获取存在相同地面景象的连续两帧光电图像,并对前后帧图像分别进行点特征、线特征检测,对提取的图像特征进行判断,提取有效的图像特征;然后对提取的图像特征进行特征关联,根据关联的图像特征像素位置计算图像特征的像素位移矢量,剔除偏差较大的位移矢量;最后根据光电设备参数及位移矢量特性计算无人机对地速度。利用无人机搭载光电设备进行了飞行试验,试验结果表明本文方法减少了计算量,具有较好实用性,能够满足无人机等低空飞行平台自主测速要求。 相似文献
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针对目标与背景两类图像模式识别问题,在已有的特征选择方法基础上,提出了一种新颖的基于免疫分子编码机理的图像特征选择方法(Immune Antibody Construction Algorithm,IACA).该方法借鉴生物免疫系统的抗体分子编码机理,在对样本进行参数估计情况下,提出熵度量单个特征对于目标和背景的识别敏感度;从集合的角度研究并且定义了特征之间的包含和互补关系;并且基于组成抗体分子氨基酸结合能量最小原则,提出了关于图像目标的免疫抗体构建规则;最终实现了寻找最优特征子集的算法IACA,该特征子集的维数通过算法自动获得无需人为设定,选择结果为目标的"免疫抗体",能很好的从背景中识别目标.利用归纳法证明了用IACA得到的特征子集的最优性.与其他特征选择方法比较,测试结果显示该算法具有较低的计算复杂度和错误识别率,表明了该方法的优越性和先进性. 相似文献
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由于网络信息量巨大,为了快速找到所需信息,需要采用数据挖掘技术。在众多数据挖掘技术中,关联规则挖掘方法应用十分广泛。所以,在多媒体图像挖掘中应用关联规则十分重要。本文对图像挖掘和关联规则进行了简单介绍,并详细阐述了多媒体图像挖掘中的关联规则挖掘。 相似文献
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由于网络信息量巨大,为了快速找到所需信息,需要采用数据挖掘技术。在众多数据挖掘技术中,关联规则挖掘方法应用十分广泛。所以,在多媒体图像挖掘中应用关联规则十分重要。本文对图像挖掘和关联规则进行了简单介绍,并详细阐述了多媒体图像挖掘中的关联规则挖掘。 相似文献
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Yang Z. Tang W.H. Shintemirov A. Wu Q.H. 《IEEE transactions on systems, man and cybernetics. Part C, Applications and reviews》2009,39(6):597-610
This paper presents a novel association rule mining (ARM)-based dissolved gas analysis (DGA) approach to fault diagnosis (FD) of power transformers. In the development of the ARM-based DGA approach, an attribute selection method and a continuous datum attribute discretization method are used for choosing user-interested ARM attributes from a DGA data set, i.e. the items that are employed to extract association rules. The given DGA data set is composed of two parts, i.e. training and test DGA data sets. An ARM algorithm namely Apriori-Total From Partial is proposed for generating an association rule set (ARS) from the training DGA data set. Afterwards, an ARS simplification method and a rule fitness evaluation method are utilized to select useful rules from the ARS and assign a fitness value to each of the useful rules, respectively. Based upon the useful association rules, a transformer FD classifier is developed, in which an optimal rule selection method is employed for selecting the most accurate rule from the classifier for diagnosing a test DGA record. For comparison purposes, five widely used FD methods are also tested with the same training and test data sets in experiments. Results show that the proposed ARM-based DGA approach is capable of generating a number of meaningful association rules, which can also cover the empirical rules defined in industry standards. Moreover, a higher FD accuracy can be achieved with the association rule-based FD classifier, compared with that derived by the other methods. 相似文献
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针对双色中波红外图像特征空间维数高,不易于对其双波段成像差异进行综合分析的问题,提出了一种基于赋权思想及雷达图的双波段图像差异纹理特征的分析方法。该方法首先构造一个特征选择矩阵,利用其选择出能够满足双波段图像差异分布规律的有效纹理特征;然后利用赋权思想将差异不显著的纹理特征去除;最后采用雷达图对保留下的差异特征进行高维显示,并由雷达图中多边形的形状信息得到维数较少的图形特征。实验数据表明,降维后的特征能够综合反映双波段图像的纹理差异幅度,为后期差异特征驱动的多级融合方法探索奠定了基础。 相似文献
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Image segmentation using association rule features 总被引:4,自引:0,他引:4
Rushing J.A. Ranganath H. Hinke T.H. Graves S.J. 《IEEE transactions on image processing》2002,11(5):558-567
A new type of texture feature based on association rules is described. Association rules have been used in applications such as market basket analysis to capture relationships present among items in large data sets. It is shown that association rules can be adapted to capture frequently occurring local structures in images. The frequency of occurrence of these structures can be used to characterize texture. Methods for segmentation of textured images based on association rule features are described. Simulation results using images consisting of man made and natural textures show that association rule features perform well compared to other widely used texture features. Association rule features are used to detect cumulus cloud fields in GOES satellite images and are found to achieve higher accuracy than other statistical texture features for this problem. 相似文献
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This paper presents a new framework for capturing intrinsic visual search behavior of different observers in image understanding by analysing saccadic eye movements in feature space. The method is based on the information theory for identifying salient image features based on which visual search is performed. We demonstrate how to obtain feature space fixation density functions that are normalized to the image content along the scan paths. This allows a reliable identification of salient image features that can be mapped back to spatial space for highlighting regions of interest and attention selection. A two-color conjunction search experiment has been implemented to illustrate the theoretical framework of the proposed method including feature selection, hot spot detection, and back-projection. The practical value of the method is demonstrated with computed tomography image of centrilobular emphysema, and we discuss how the proposed framework can be used as a basis for decision support in medical image understanding. 相似文献
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针对目前基于小波变换图像融合增强算法原始图 像中的多尺度细节信息的不足,提 出了一种改进的多尺度小波变换与深度残差选择相结合的图像增强算法。利用小波变换对原 始图像进行分解提取得到它的多级分解系数后,再利用不同规则对不同层次的小波系数进行 重构,与此同时引入深度残差算法的思想对子带系数做残差。对于高频子带系数,计算子带 残差的系数与梯度特征融合方法的系数,选用两者最大值进行融合增强;而对于低频子带系 数则采用梯度特征融合增强系数与子带残差系数取平均值的算法进行融合。通过在MATLAB 平台上的实验对所提出算法进行验证,峰值信噪比相较于对比的方法都有所提高,且均方根 误差也得到减小,结构相似度都得到提高,结果表明该算法能增强图像的多尺度细节信息, 提高图像的信噪比,且具有更好的图像增强效果。 相似文献
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提出一种基于K-means Clustering和脉冲耦合神经网络(PCNN)的图像融合的方法,首先,以多特征信息为聚类方式利用K-means Clustering分割提取源图像的对应特征点,通过归类合并建立多模医学图像的特征点集合,根据特征点分布将图像划分为纹理区域和非纹理区域,纹理区域对应系数输入PCNN得到点火映射图,根据点火次数选择融合系数,非纹理区域的系数通过双通道PCNN进行融合。实验结果表明,该算法能够精确划分图像纹理区域,进而利用PCNN和双通道PCNN在图像不同区域系数选择各自的优势,融合图像纹理清晰,质量改善。 相似文献
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为确保源图像中的显著区域在融合图像保持显著,提出了一种自注意力引导的红外与可见光图像融合方法。在特征学习层引入自注意力学习机制获取源图像的特征图和自注意力图,利用自注意力图可以捕获到图像中长距离依赖的特性,设计平均加权融合策略对源图像的特征图进行融合,最后将融合后的特征图进行重构获得融合图像。通过生成对抗网络实现了图像特征编码、自注意力学习、融合规则和融合特征解码的学习。TNO真实数据上的实验表明,学习到注意力单元体现了图像中显著的区域,能够较好地引导融合规则的生成,提出的算法在客观和主观评价上优于当前主流红外与可见光图像融合算法,较好地保留了可见光图像的细节信息和红外图像的红外目标信息。 相似文献
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In this article, we propose a novel system for feature selection, which is one of the key problems in content-based image
indexing and retrieval as well as various other research fields such as pattern classification and genomic data analysis.
The proposed system aims at enhancing semantic image retrieval results, decreasing retrieval process complexity, and improving
the overall system usability for end-users of multimedia search engines. Three feature selection criteria and a decision method
construct the feature selection system. Two novel feature selection criteria based on inner-cluster and intercluster relations
are proposed in the article. A majority voting-based method is adapted for efficient selection of features and feature combinations.
The performance of the proposed criteria is assessed over a large image database and a number of features, and is compared
against competing techniques from the literature. Experiments show that the proposed feature selection system improves semantic
performance results in image retrieval systems.
This work was supported by the Academy of Finland, Project No. 213,462 (Finnish Centre of Excellence Program 2006–2011). 相似文献
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Hyperion影像的光谱分辨率高,数据体积庞大,而且相邻波段之间的相关性强,信息冗余度较高, 给数据处理与解译带来了很多问题。鉴于此,提出了通过将分段主成分分析和波段指数相结合来开展波段选择与降维研究的思想。 同时采用自适应波段选择法、波段指数法和主成分分析累计贡献率方法进行了波段选择方法的对比研究;对4种波段选择方法所得到的结 果进行了最佳波段组合、地物可分性和图像变换比较分析。实验结果表明,分段主成分分析与波段指数综合方法可以有效抑制由于全局变换造成局部重要光谱被滤除的现象 ,同时还可兼顾自适应分区后各子区间及区间内波段之间的相关性,有效降低高光谱数据的维度。由此可见,该方法的波段选择效 果优于传统的自适应波段选择方法、波段指数法以及主成分分析累计贡献率方法。 相似文献