共查询到20条相似文献,搜索用时 125 毫秒
1.
2.
3.
4.
针对采用准zemike多项式拟和法求主动光学校正力的过程中,因为准zernike多项式的不正交性造成求解误差大、求解不稳定的问题,提出了对准zernike多项式进行householder变换的方法.该方法不同于传统的最小二乘法和Gram-Schmidt正交化方法,它避免了因构造法方程组出现严重病态而引入的计算误差.根据该方法求出主镜的刚度矩阵,然后采用阻尼最小二乘法求校正力.基于此方法对直径为400mm的实验镜进行了多次仿真计算,计算结果表明,采用householder变换后波面拟和精确,求解稳定,校正效果较好. 相似文献
5.
针对传统医学图像弹性配准方法中存在配准不连续、配准过程复杂,且配准用时较长等问题,提出基于光流场模型的医学图像弹性配准方法。首先通过加权矩阵控制对医学图像梯度进行平滑处理,构建光流场模型;采用该模型确定医学图像目标的具体运动情况;然后计算图像序列中不同像素点光流场,设置医学图像光流场的初始条件和边界条件;最后对医学图像进行几何变化,获取医学图像的目标函数,完成基于光流场模型的医学图像弹性配准。实验结果表明:采用本文方法对医学图像进行弹性配准的效果较为理想,获取的医学图像较为清晰,且配准的工作效率较高。 相似文献
6.
7.
8.
将1维的OPT推广为2维OPT,在此基础上提出了一种基于正交多项式变换的图像融合算法.正交多项式变换将图像的主要特征映射到时域特征空间,而将图像的细节特征映射为白噪声.融合处理在特征空间中进行.实验结果表明,在降噪方面该算法优于离散小波变换方法、拉普拉斯金字塔方法和Morphological金字塔方法. 相似文献
9.
纪利娥杨风暴王志社陈磊 《电视技术》2013,(19):27-31
特征点是图像的一种重要局部特征,特征点检测是基于特征点图像配准的关键技术。通过特征点的提取与处理,对把握图像的局部及整体特征,特别对图像配准及目标识别等领域都具有重要的实际意义。详细介绍了图像配准中主流的特征点提取方法,并分析其优缺点。通过实验,利用特征点评价方法对各种算法的性能进行比较,对图像配准的研究具有一定的指导意义。 相似文献
10.
图像配准中特征点检测算法的探讨 总被引:1,自引:1,他引:0
特征点是图像的一种重要局部特征,特征点检测是基于特征点图像配准的关键技术.通过特征点的提取与处理,对把握图像的局部及整体特征,特别对图像配准及目标识别等领域都具有重要的实际意义.详细介绍了图像配准中主流的特征点提取方法,并分析其优缺点.通过实验,利用特征点评价方法对各种算法的性能进行比较,对图像配准的研究具有一定的指导意义. 相似文献
11.
Image analysis by Krawtchouk moments 总被引:19,自引:0,他引:19
A new set of orthogonal moments based on the discrete classical Krawtchouk polynomials is introduced. The Krawtchouk polynomials are scaled to ensure numerical stability, thus creating a set of weighted Krawtchouk polynomials. The set of proposed Krawtchouk moments is then derived from the weighted Krawtchouk polynomials. The orthogonality of the proposed moments ensures minimal information redundancy. No numerical approximation is involved in deriving the moments, since the weighted Krawtchouk polynomials are discrete. These properties make the Krawtchouk moments well suited as pattern features in the analysis of two-dimensional images. It is shown that the Krawtchouk moments can be employed to extract local features of an image, unlike other orthogonal moments, which generally capture the global features. The computational aspects of the moments using the recursive and symmetry properties are discussed. The theoretical framework is validated by an experiment on image reconstruction using Krawtchouk moments and the results are compared to that of Zernike, pseudo-Zernike, Legendre, and Tchebyscheff moments. Krawtchouk moment invariants are constructed using a linear combination of geometric moment invariants; an object recognition experiment shows Krawtchouk moment invariants perform significantly better than Hu's moment invariants in both noise-free and noisy conditions. 相似文献
12.
针对通道幅相误差和图像配准误差等非理想因素导致地面动目标检测性能下降的问题,该文结合最小方差和空域导向矢量两种杂波抑制算法,提出一种基于通道误差校准的空域导向矢量杂波抑制方法。该方法首先计算最小方差杂波抑制的权向量,通过该权向量构造配准图像,然后利用配准图像计算杂波正交补空间,最后通过正交子空间的方法实现杂波抑制。理论分析及实验结果表明,所提方法在图像配准误差和通道幅相误差较大的情况下仍具有很好的检测性能,能获得较最小方差杂波抑制方法和基于空域导向矢量的杂波抑制方法更高的信杂噪比。 相似文献
13.
Xifa Duan Zheng Tian Mingtao Ding Wei Zhao 《AEUE-International Journal of Electronics and Communications》2013,67(1):20-28
For pre- and post-earthquake remote-sensing images, registration is a challenging task due to the possible deformations of the objects to be registered. To overcome this problem, a registration method based on robust weighted kernel principal component analysis is proposed to precisely register the variform objects. Firstly, a robust weighted kernel principal component analysis (RWKPCA) method is developed to capture the common robust kernel principal components (RKPCs) of the variform objects. Secondly, a registration approach is derived from the projection on RKPCs. Finally, two experiments are conducted on the SAR image registration in Wenchuan earthquake on May 12, 2008, and the results showed that the method is very effective in capturing structure patterns and generalized well for registration. 相似文献
14.
15.
16.
R. Krishnamoorthi S. Sathiya devi 《Journal of Visual Communication and Image Representation》2012,23(1):18-30
In this paper, a simple and an efficient Content Based Image Retrieval which is based on orthogonal polynomials model is presented. This model is built with a set of carefully chosen orthogonal polynomials and is used to extract the low level texture features present in the image under analysis. The orthogonal polynomials model coefficients are reordered into multiresolution subband like structure. Simple statistical and perceptual properties are derived from the subband coefficients to represent the texture features and these features form a feature vector. The efficiency of the proposed feature vector extraction for texture image retrieval is experimented on the standard Brodatz and MIT’s VisTex texture database images with the Canberra distance measure. The proposed method is compared with other existing retrieval schemes such as Discrete Cosine Transformation (DCT) based multiresolution subbands, Gabor wavelet and Contourlet Transform based retrieval schemes and is found to outperform the existing schemes with less computational cost. 相似文献
17.
Meyer CR Leichtman GS Brunberg JA Wahl RL Quint LE 《IEEE transactions on medical imaging》1995,14(1):1-11
The authors have extended point-based registration to include simultaneous registration of points, lines, and planes, to permit accurate and easily implemented three-dimensional (3-D) registration of multimodal data sets for fusion of clinical anatomic and functional imaging modalities. Constructive geometry is used to define user-identified features where each feature's role in the reconstruction is weighted based on its relative statistical quality, i.e., variance. The algorithm employs singular value decomposition (SVD) and optimization techniques to find the minimum weighted least mean square error (LMSE) affine solution. The new method is generally more accurate due to the availability of more features to register. Notably the error surface contains only one minimum. Different subclasses of affine solutions can be obtained based on appropriateness and sufficiency of the number and type of input features. Preliminary results indicate that this method is useful in multimodal diagnostic image fusion. 相似文献
18.
19.
SAR图像中目标配准的稳健加权核主成分分析方法 总被引:2,自引:2,他引:0
针对震前震后合成孔径雷达(SAR)图像中发生复 杂形变的目标,提 出了基于稳健的加权核主成分分析(KPCA)的配准方法。首先,提出 一种稳健的 加权KPCA(RWKPCA)方法,不仅能获得震前震后形变目标的共同稳健核主成分(RKPC s),还可 以作为异常值判别准则;其次,利用在共同RKPCs上的投影定义震前震后形变目标特 征的相似性度 量;最后,利用特征的相似性度量精确配准形变目标。对2008年5月12日汶川地震前后的S AR图像进行配准并与现有方法进行比较,结果表明,本文方法能够有效的得到形变目标的 共同RKPCs,并得到很好的配准结果。 相似文献
20.
Image registration is a challenging problem for computer vision, and accurate and effective image registration is still required in various computer vision applications, e.g., 3-D scanning, autonomous navigation, and augmented reality. However, image registration becomes difficult due to the presence of noise and photometric changes. This paper presents a novel image registration method with unsupervised inverse intensity compensation (ICIR). This methodology uses weighted vectors to compensate for areas affected by radiometric variations. This is a 5-D vector body composed of RGB, brightness, and gradient, that is, each pixel is represented by a 5-D vector in its neighborhood. When performing image registration, the vector angle metric robust to illumination effect is used to calculate cost volumes. Then the selected cost metrics are aggregated based on RGB-Gradient tree structure. Experiments performed on stereo images of the Middlebury datasets and ours demonstrate this methodology in calculation accuracy and time all have good performance. 相似文献