自由视角多平面场景图像拼接技术研究
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摘要
图像拼接技术研究解决的主要问题是如何将针对同一场景，相互间有部分重叠的小视域照片合成为一幅大视场的高分辨率图像，以满足大众观察浏览大视场图像场景的需求，这一技术在虚拟现实、医学图像处理、遥感技术以及军事领域均有广泛的应用，是计算机视觉、图像处理和计算机图形学的研究热点。
在约束条件下，图像的匹配和拼接都比较准确和鲁棒，然而无论室内或室外场景，自然环境又或是人工环境下，总存在着丰富的平面结构信息，对于实际具有深度变化的非平面场景，当相机以任意角度拍摄时，错误的平面假设不能形成正确的透视关系和景物遮挡关系，无法实现场景的有效拼接。针对传统拼接算法的局限性，本文开展自由视角多平面场景图像拼接技术研究，降低对拍摄者和拍摄条件的要求，使拼接具有较强的实用性和灵活性。
本文的主要创新点如下：
（1）提出一种基于特征点引导采样的分层多平面图像配准方法。根据平面结构的相似度，改进匹配点的采样规则，通过对初匹配特征点的平面划分以寻找场景的多个投影面，实现了场景中平面区域的准确检测和配准。算法减少了图像拼接的重投影畸变，不仅能够快速精确地确定每个平面的变换模型，同时大幅度增加了正确匹配点对的数目，有效地解决了漏匹配的问题。
（2）提出一种基于共享最近邻层次聚类的多平面图像配准方法。以单应矩阵为约束模型，并引入度量相似度的间接指标-共享最近邻相似度，在定义相似度量时考虑了点的环境，对稀疏特征点在相似概念空间中分层聚类，得到多个近平面场景的特征点集。算法无需事先指定模型数量，可自适应实现多模型参数的鲁棒估计，能够自动完成对整个场景多平面区域的匹配和跟踪。
（3）提出基于几何结构特征匹配的图像缝合技术，可适用于单平面和多平面场景。在分析典型亮度不一致性的基础上，采用曲率作为缝合线累计误差的匹配特征，可有效避免曝光时间差异和镜头晕影带来的误匹配问题。针对多个平面场景的情况，在每个配准得到的投影矩阵对应的重叠区域中搜索匹配累计误差最小的缝合线的同时，增加缝合线穿过平面数最少的约束条件，可解决现有方法处理出现的结构误差问题。
Image mosaic is a kind of technique that can synthesize a number oflow-resolution images with overlapped regions from the same scene into ahigh-resolution image. The advantage of this technique can meet the requirementof the observation for the larger image scene. Currently, image mosaic has beenwidely applied in virtual reality, medical image processing, remote sensing andmilitary applications, and it also has become a hot research topic in academicfields, such as computer vision, image processing and computer graphics.
In the constraint conditions, the image matching and stitching are moreaccurate and robust. However, no matter in the indoor or outdoor scenes, and thenatural or artificial environment, there are abundant multiple planar structures,rather than one simple planar structure. Therefore, regarding the scene of multipleplanar structures with depth variation, the feature points in the images capturedfrom the scene with different viewing angles will not satisfied with therelationship of the perspective projection transform. It can not achieve the correctperspective and occlusion relationships, so that the following registration will fail.According to the limitation of the existing mosaic algorithms, study of multipleplanar scene image mosaic technology to carry out the view of freedom in thispaper, to reduce the photographer and shooting conditions, the splicing has strongpracticability and flexibility.
The main innovation of this article are as follows:
(1) We propose a guided sampling based planar structure detection methodusing multiple homographic matrices for image registration. In the proposedmethod, the sorted residual error information is used to guide the sampling ofmatching feature points, and the similar matching points are added to the point setfor sampling. Thus, the inlier probability of sampling point set in our method ishigh, and the parameter model of the optimal homographic matrix can be obtained efficiently.
(2) We propose a new method to detect multi-planar regions for imageregistration based on hierarchical clustering for shared nearest neighbor (SNN).The proposed method uses the homographic matrix as the constraint model andestablishes the similar conceptual space. The feature point sets of severalapproximate planes can be obtained after hierarchical clustering for the sparsefeature points. The proposed method doesn’t need to pre-determine the number ofplanar regions for detection. Our method can detect and alignment the planarregions accurately and realize the optimal estimation of multi-model parameters
(3) We propose a new method of optimal structure seam selection for imagestitching. For the single planar scence, through analyzing the illuminationinconsistency for exposure time diference and lens vignetting, we adopt thecurvanture value as the matching feature in accumulated error calculation foroptimal seam, which can achieve better robustness. For the multiple planar scence,based on the results of multiple planar image registration, we search for the bestseam which not only meets the minimal structure differences, but also meets therequirement that it should pass through minimum planes. The method can choosethe best projection matrix from the matrixes corresponding to different planesautomatically to complete the image stitching. This method can reduce thestructure errors in multi-planar stitching caused by traditional stitching method.
在约束条件下，图像的匹配和拼接都比较准确和鲁棒，然而无论室内或室外场景，自然环境又或是人工环境下，总存在着丰富的平面结构信息，对于实际具有深度变化的非平面场景，当相机以任意角度拍摄时，错误的平面假设不能形成正确的透视关系和景物遮挡关系，无法实现场景的有效拼接。针对传统拼接算法的局限性，本文开展自由视角多平面场景图像拼接技术研究，降低对拍摄者和拍摄条件的要求，使拼接具有较强的实用性和灵活性。
本文的主要创新点如下：
（1）提出一种基于特征点引导采样的分层多平面图像配准方法。根据平面结构的相似度，改进匹配点的采样规则，通过对初匹配特征点的平面划分以寻找场景的多个投影面，实现了场景中平面区域的准确检测和配准。算法减少了图像拼接的重投影畸变，不仅能够快速精确地确定每个平面的变换模型，同时大幅度增加了正确匹配点对的数目，有效地解决了漏匹配的问题。
（2）提出一种基于共享最近邻层次聚类的多平面图像配准方法。以单应矩阵为约束模型，并引入度量相似度的间接指标-共享最近邻相似度，在定义相似度量时考虑了点的环境，对稀疏特征点在相似概念空间中分层聚类，得到多个近平面场景的特征点集。算法无需事先指定模型数量，可自适应实现多模型参数的鲁棒估计，能够自动完成对整个场景多平面区域的匹配和跟踪。
（3）提出基于几何结构特征匹配的图像缝合技术，可适用于单平面和多平面场景。在分析典型亮度不一致性的基础上，采用曲率作为缝合线累计误差的匹配特征，可有效避免曝光时间差异和镜头晕影带来的误匹配问题。针对多个平面场景的情况，在每个配准得到的投影矩阵对应的重叠区域中搜索匹配累计误差最小的缝合线的同时，增加缝合线穿过平面数最少的约束条件，可解决现有方法处理出现的结构误差问题。
Image mosaic is a kind of technique that can synthesize a number oflow-resolution images with overlapped regions from the same scene into ahigh-resolution image. The advantage of this technique can meet the requirementof the observation for the larger image scene. Currently, image mosaic has beenwidely applied in virtual reality, medical image processing, remote sensing andmilitary applications, and it also has become a hot research topic in academicfields, such as computer vision, image processing and computer graphics.
In the constraint conditions, the image matching and stitching are moreaccurate and robust. However, no matter in the indoor or outdoor scenes, and thenatural or artificial environment, there are abundant multiple planar structures,rather than one simple planar structure. Therefore, regarding the scene of multipleplanar structures with depth variation, the feature points in the images capturedfrom the scene with different viewing angles will not satisfied with therelationship of the perspective projection transform. It can not achieve the correctperspective and occlusion relationships, so that the following registration will fail.According to the limitation of the existing mosaic algorithms, study of multipleplanar scene image mosaic technology to carry out the view of freedom in thispaper, to reduce the photographer and shooting conditions, the splicing has strongpracticability and flexibility.
The main innovation of this article are as follows:
(1) We propose a guided sampling based planar structure detection methodusing multiple homographic matrices for image registration. In the proposedmethod, the sorted residual error information is used to guide the sampling ofmatching feature points, and the similar matching points are added to the point setfor sampling. Thus, the inlier probability of sampling point set in our method ishigh, and the parameter model of the optimal homographic matrix can be obtained efficiently.
(2) We propose a new method to detect multi-planar regions for imageregistration based on hierarchical clustering for shared nearest neighbor (SNN).The proposed method uses the homographic matrix as the constraint model andestablishes the similar conceptual space. The feature point sets of severalapproximate planes can be obtained after hierarchical clustering for the sparsefeature points. The proposed method doesn’t need to pre-determine the number ofplanar regions for detection. Our method can detect and alignment the planarregions accurately and realize the optimal estimation of multi-model parameters
(3) We propose a new method of optimal structure seam selection for imagestitching. For the single planar scence, through analyzing the illuminationinconsistency for exposure time diference and lens vignetting, we adopt thecurvanture value as the matching feature in accumulated error calculation foroptimal seam, which can achieve better robustness. For the multiple planar scence,based on the results of multiple planar image registration, we search for the bestseam which not only meets the minimal structure differences, but also meets therequirement that it should pass through minimum planes. The method can choosethe best projection matrix from the matrixes corresponding to different planesautomatically to complete the image stitching. This method can reduce thestructure errors in multi-planar stitching caused by traditional stitching method.
引文
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