共查询到19条相似文献,搜索用时 156 毫秒
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针对一组多光谱遥感图像中,各谱段图像之间配准不一致的问题,本文提出了一种基于特征点的快速自动配准方法。在图像信息熵的基础上,利用环形移动窗口,自动快速寻找感兴趣区域, 并利用尺度不变特征转换(SIFT)算法提取特征。为提高精度,文中对特征初匹配方法作了改进,并用余弦定理和空间距离约束条件剔除误匹配点,之后提取最稳定的特征点对计算变换参数,完成配准。最后根据配准前后图像的互信息和特征点的均方根误差(RMSE)来衡量配准的程度。通过对大量中巴地球资源卫星拍摄的多光谱图像进行实验,该方法能达到亚像素级配准精度,并能快速对各谱段图像进行配准。 相似文献
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面向光学图像的多时相、多光谱、多传感器图像的自动配准,本文描述一个基于特征的高精度图像配准算法.它以点映射配准技术为基础,处理具有全局仿射几何失真的图像配准问题.首先,通过边缘检测和相应的后处理提取封闭边界;其次,根据边界链码相关和区域不变矩匹配策略建立边界的对应,并对对应重心即匹配点对进行一致性检测获得基元控制点;最后,估计初始变换参数,并通过显著点片的相关匹配来增加控制点个数,迭代修正变换参数以提高配准精度.多种遥感图像数据的配准实验和对比试验证实了的自动算法具有较高的可靠性和配准精度. 相似文献
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基于椭圆傅里叶描述子的遥感图像配准算法 总被引:4,自引:4,他引:0
传统的基于点特征的图像配准算法在遥感图像配 准时提取的特征点数量大、分布密,易产生误匹配,导致特 征匹配的效率和精度低。为此,本文利用椭圆傅里叶描述子(EFD)能较好保留 形状信息的特点,提出了一种基于EFD的 图像配准算法,根据匹配的边界对预估变换参数,给出特征搜索范围,从而有效地提 高特征搜索的效率。实 验结果表明,所提出算法能有效抑制误匹配的产生,提升特征匹配的效率,尤其是对于纹理 丰富的大尺寸图像,提 升效果更加明显,验证了本文算法对遥感图像配准的适用性。 相似文献
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多光谱成像技术是遥感领域的一项重要技术。多光谱图像配准技术可以提高遥感图像的应用效率和能力。基于边缘结构在多光谱图像中较为稳定这一特性,提出了一种基于对称性边缘的多光谱图像配准方法,该方法主要包含“图像比例调整”、“对称性边缘提取”和“互信息配准”等三个步骤。基于天宫二号宽波段成像仪的遥感数据设计了一种多子图配准方案,验证了所提方法在可见光、短波红外和长波红外三个谱段之间图像配准的有效性。设置对比实验,将所提配准方法与其他多光谱图像配准方法进行比较,结果表明该方法在天宫二号宽波段遥感图像的配准中具有较高的精度。 相似文献
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Image registration using log-polar mappings for recovery of large-scale similarity and projective transformations. 总被引:3,自引:0,他引:3
This paper describes a novel technique to recover large similarity transformations (rotation/scale/translation) and moderate perspective deformations among image pairs. We introduce a hybrid algorithm that features log-polar mappings and nonlinear least squares optimization. The use of log-polar techniques in the spatial domain is introduced as a preprocessing module to recover large scale changes (e.g., at least four-fold) and arbitrary rotations. Although log-polar techniques are used in the Fourier-Mellin transform to accommodate rotation and scale in the frequency domain, its use in registering images subjected to very large scale changes has not yet been exploited in the spatial domain. In this paper, we demonstrate the superior performance of the log-polar transform in featureless image registration in the spatial domain. We achieve subpixel accuracy through the use of nonlinear least squares optimization. The registration process yields the eight parameters of the perspective transformation that best aligns the two input images. Extensive testing was performed on uncalibrated real images and an array of 10,000 image pairs with known transformations derived from the Corel Stock Photo Library of royalty-free photographic images. 相似文献
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基于对数极坐标变换的图像匹配算法 总被引:1,自引:0,他引:1
相位相关算法通常只具有平移不变性,而不具有尺度和旋转不变性,因此无法对存在尺度和旋转变化的图像进行图像匹配.而对数极坐标变换可以将图像在笛卡儿坐标系下的尺度和旋转变化变换为沿对数极坐标系的平移运动,具有较好的尺度和旋转不变性.文中提出了一种基于图像对数极坐标变换的相关匹配算法.仿真结果表明基于对数极坐标变换的相位相关算法可以针对具有尺度和旋转变换的图像进行很好的匹配,并能检测出图像的旋转角度及尺度参数. 相似文献
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I Maglogiannis S Pavlopoulos D Koutsouris 《IEEE transactions on information technology in biomedicine》2005,9(1):86-98
This paper describes an integrated prototype computer-based system for the characterization of skin digital images. The first stage includes an image acquisition arrangement designed for capturing skin images, under reproducible conditions. The system processes the captured images and performs unsupervised image segmentation and image registration utilizing an efficient algorithm based on the log-polar transform of the images' Fourier spectrum. Border- and color-based features, extracted from the digital images of skin lesions, were used to construct a classification module for the recognition of malignant melanoma versus dysplastic nevus. Different methods, drawn from the fields of artificial intelligence (neural networks) and statistical modeling (discriminant analysis), were used in order to find the best classification rules and to compare the results of different approaches to the problem. 相似文献
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针对加速鲁棒性特征算法,在没有后续去误匹配等处理的情况下,对存在较大旋转角度的两幅待匹配图像,匹配精度较低的问题,提出了一种基于傅里叶梅林变换的SURF算法。该算法通过对待匹配图像和参考图像实施傅里叶变换和梅林变换,利用能量谱求出两幅图像发生的旋转角度,并利用SURF算法找出图像间发生的平移和尺度变化,实现了图像间的匹配。实验结果表明,该算法可有效地实现图像间存在较大旋转角度时的几何匹配,且相比已有的SIFT和SURF算法,具有更好的匹配效果。 相似文献
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Image Registration Using Adaptive Polar Transform 总被引:1,自引:0,他引:1
Image registration is an essential step in many image processing applications that need visual information from multiple images for comparison, integration, or analysis. Recently, researchers have introduced image registration techniques using the log-polar transform (LPT) for its rotation and scale invariant properties. However, it suffers from nonuniform sampling which makes it not suitable for applications in which the registered images are altered or occluded. Inspired by LPT, this paper presents a new registration algorithm that addresses the problems of the conventional LPT while maintaining the robustness to scale and rotation. We introduce a novel adaptive polar transform (APT) technique that evenly and effectively samples the image in the Cartesian coordinates. Combining APT with an innovative projection transform along with a matching mechanism, the proposed method yields less computational load and more accurate registration than that of the conventional LPT. Translation between the registered images is recovered with the new search scheme using Gabor feature extraction to accelerate the localization procedure. Moreover an image comparison scheme is proposed for locating the area where the image pairs differ. Experiments on real images demonstrate the effectiveness and robustness of the proposed approach for registering images that are subjected to occlusion and alteration in addition to scale, rotation, and translation. 相似文献
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Pseudopolar-based estimation of large translations, rotations, and scalings in images. 总被引:9,自引:0,他引:9
One of the major challenges related to image registration is the estimation of large motions without prior knowledge. This paper presents a Fourier-based approach that estimates large translations, scalings, and rotations. The algorithm uses the pseudopolar (PP) Fourier transform to achieve substantial improved approximations of the polar and log-polar Fourier transforms of an image. Thus, rotations and scalings are reduced to translations which are estimated using phase correlation. By utilizing the PP grid, we increase the performance (accuracy, speed, and robustness) of the registration algorithms. Scales up to 4 and arbitrary rotation angles can be robustly recovered, compared to a maximum scaling of 2 recovered by state-of-the-art algorithms. The algorithm only utilizes one-dimensional fast Fourier transform computations whose overall complexity is significantly lower than prior works. Experimental results demonstrate the applicability of the proposed algorithms. 相似文献
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对数极坐标域下的图像配准方法常因相位相关互功率谱呈现多峰分布而影响匹配准确度,为此提出了一种基于区域最优峰值的相位相关红外图像配准方法。首先将待配准图像和参考图像转换到对数极坐标域,其次以自适应巴特沃斯高通滤波为预处理,最后结合归一化互相关和相位相关的相似性测度,在合理截断互功率谱半径轴低数值段的基础上,筛选出最优峰值实现自动配准,同时研究了对数极坐标变换尺寸对匹配性能的影响,给出了最优尺寸变换比。实验结果表明:该算法对噪声污染图像表现出较好的鲁棒性,对于存在平移、旋转和缩放的红外图像具有更高的配准精度。 相似文献
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LK光流算法是一种精确高效的特征跟踪算法,能够较大幅度提高图像配准的精度和速度。针对时间序列图像的配准问题,基于LK光流算法,通过基于图像金字塔的方式跟踪改进后的FAST特征角点,采用一种鲁棒的单应矩阵估计算法解算配准参数,提出了一种基于LK光流和改进FAST特征的实时鲁棒配准算法。通过一组时间序列图像从配准精度和配准速度两个方面对所提出算法的性能进行了验证分析,平均重投影误差为0.16,平均处理速度为30 Hz。实验结果表明,该算法能够提取稳定的FAST角点,快速准确地跟踪匹配序列图像之间的特征,较好地解决时间序列图像的实时配准问题。 相似文献