一种快速区域立体匹配算法设计及实现

为了精确建立两幅图像像素间的对应关系,克服区域立体匹配算法计算量大的缺点,提出了一种改进的区域立体匹配算法。改进的区域匹配算法运用双向立体匹配策略来提高两幅图像像素间的匹配精度,并结合mean-shift图像分割技术,在同一区域具有相同视差的假设前提下获得图像的稠密视差;为了克服区域立体匹配计算量大的缺点,该算法引入伪极线约束将真正匹配点的位置限定在一个非常小的范围内,从而大大减少了匹配点的搜索范围,有效地降低了匹配算法的计算量。实验结果表明,改进的双向匹配算法可以有效地缩小匹配搜索范围,并实现图像间的精确稠密匹配。     

一种改进的完全搜索块匹配算法

完全搜索块匹配算法是图像序列稳定中常用的运动估计方法,在传统的完全搜索块匹配算法中,在搜索区域中图像序列的当前帧和参考帧对应的像素对对匹配结果的贡献是完全一样的,这样使得算法的性能容易受到待稳定的图像序列中各种噪声的影响。针对这个不足,提出了一种改进的完全搜索块匹配算法。在新的匹配准则中,搜索区域中图像序列的当前帧和参考帧对应的像素对对匹配结果是否有贡献取决于它们灰度值之差的绝对值与预先设定的门限值进行大小比较的结果,对应的灰度值之差的绝对值不超过该门限值的像素对对匹配结果有贡献,而且贡献大小受到与像素对位置相关的加权处理,否则该像素对对匹配结果无贡献。实验结果证明了该算法的优越性。     

彩色立体图像匹配算法研究

立体图像匹配对于自由立体重建、三维测量以及立体显示中图像压缩来说是非常重要的。针对区域灰度互相关图像匹配的计算量大、速度慢的情况,运用了一组快速灰度互相关计算公式,提出了用视差限制搜索空间。同时,针对彩色图像的特点,将彩色图像的色彩信息考虑进图像的匹配过程中,将彩色图像的R、G、B三单色图像分别进行灰度相关匹配,定义并采用了颜色分量权重系数来抑制误匹配点。实验表明,该方法有效地减少了计算量,加快了计算速度,提高了图像匹配精度,具有较好的实时性。该方法将应用于三维立体显示中基于视差图的视差进行图像压缩。     

Matching images based on consistency graph and region adjacency graphs

The image matching methods based on regions have many advantages over the point matching techniques, and the most charming one is that once region being matched, all pixels are matched in theory. It would benefit many applications, such as object retrieval, stereo corresponding, semantic understanding a scene, object tracking. This paper proposes a new region matching algorithm based on consistency graph and region adjacency graphs. Firstly, the segmented images are transformed into region adjacency graphs, and the potential region pairs and the potential edge segment pairs are packaged in a consistency graph. Since the rightly matched pair always is accompanied by harmonious neighbourhoods, the right correspondences tend to cluster together, and the error corresponding relationship should have few chances to connect to any compatible neighbourhood. Thus, the solution space is greatly reduced and the corresponding relationship can be found in a polynomial computational complexity just by a simple method, such as seed-growth method. To the best of our knowledge, the method is the first one to match two images by region adjacency graphs and find the corresponding relationship in a polynomial computational complexity. Experiments on the existing benchmark show that the proposed method could quickly find the right corresponding relationship between images with illumination, rotation and affine transformation.     

基于改进Census变换与梯度融合的立体匹配算法

双目立体匹配根据视差原理将平面视觉转化到三维立体视觉,是三维重建的核心步骤之一。针对局部立体匹配算法在深度不连续、弱纹理区域匹配精度低且易受光照、噪声等因素干扰的问题,提出了一种改进的立体匹配算法。首先,在代价计算阶段将改进的Census代价与梯度代价进行融合,并采用引导滤波算法对图像进行多尺度代价聚合;然后,采用赢家通吃算法计算初始视差;最后,采用左右一致性检测、中值滤波进行视差后处理,得到最终的视差图。实验结果表明,本算法在Middlebury2.0测试平台上的平均误匹配率为5.11%,且具有很好的稳健性和实用性。     

基于扩展相位相关的小基高比立体匹配方法

为获得高精度亚像素级视差以满足小基高比摄影测量需求,提出一种基于扩展相位相关的小基高比立体匹配方法.该方法采用分步式策略,首先利用自适应窗口匹配法计算整像素级视差,然后在整像素级视差的指导下建立同名像点之间的对应关系,再分别以左右同名像点为中心截取子图像,最后利用扩展相位相关匹配法对子图像进行亚像素级匹配,获得亚像素级视差.采用小基高比立体像对和带有亚像素级视差的模拟立体像对进行实验,结果表明基于扩展相位相关的小基高比立体匹配方法在精度和效率方面具有优越性能.     

一种基于彩色图像分割的立体匹配算法

提出了一种新的立体匹配算法.首先采用均值漂移算法将参考图像根据彩色信息快速聚类成不同区域;然后根据变窗口算法计算的匹配点,把分割区域分为可靠区域和不可靠区域,计算可靠区域的模板参数;最后在全局评价函数中加入遮挡约束,通过贪婪算法把可靠区域的模板分配给不可靠区域使得全局评价函数取到最小值.实验结果表明,该算法可较好地处理大的低纹理区域和遮挡像素,匹配精度高,克服了基于局部算法中存在的边界模糊.     

基于引导滤波及视差图融合的立体匹配

立体匹配是双目视觉领域的重要研究方向.为在保证图片纹理区域匹配精度的同时降低弱纹理区域的误匹配率,提出一种基于引导滤波及视差图融合的立体匹配方法.首先,根据图像颜色相似性将图片划分为纹理较丰富区域和弱纹理区域.接着,分别采用不同参数的引导滤波进行代价聚合及视差计算,得到两张视差图.然后依据纹理区域划分的结果对获得的两张视差图进行融合.最后,通过左右一致性检测、加权中值滤波等视差优化步骤得到最终视差图.对Middlebury测试平台上标准图像对的实验结果表明,该方法在6组弱纹理图像上的平均误匹配率为9.67％,较传统引导滤波立体匹配算法具有更高的匹配精度.     

High‐Quality Stereo Depth Map Generation Using Infrared Pattern Projection

In this paper, we present a method for obtaining a highquality 3D depth. The advantages of active pattern projection and passive stereo matching are combined and a system is established. A diffractive optical element (DOE) is developed to project the active pattern. Cross guidance (CG) and auto guidance (AG) are proposed to perform the passive stereo matching in a stereo image in which a DOE pattern is projected. When obtaining the image, the CG emits a DOE pattern periodically and consecutively receives the original and pattern images. In addition, stereo matching is performed using these images. The AG projects the DOE pattern continuously. It conducts cost aggregation, and the image is restored through the process of removing the pattern from the pattern image. The ground truth is generated to estimate the optimal parameter among various stereo matching algorithms. Using the ground truth, the optimal parameter is estimated and the cost computation and aggregation algorithm are selected. The depth is calculated and bad‐pixel errors make up 4.45% of the non‐occlusion area.     

多策略ATLAS数据优选与影像匹配相结合的SAR高程控制点提取

为了精化星载SAR影像几何参数并提高立体定位精度,借鉴星载激光测高数据光学遥感影像高程控制点提取思路,设计了一种多策略高级地形激光测高系统(ATLAS)数据优选与影像匹配相结合的SAR高程控制点提取方法。该方法采用非夜间观测光子滤除、高置信度光子选取、SRTM DEM辅助的粗差剔除、大偏心率椭圆滤波核平坦区域光子筛选等多种策略,从ATLAS数据ATL03级产品中提取高质量、平坦区域的激光高程点,再依据SRTM DEM对斜距SAR影像进行地理编码,按激光高程点的平面坐标选取局部谷歌地球影像作为足印影像,采用秩自相似描述子进行足印影像与SAR地理编码影像的匹配,得到与激光高程点对应的SAR影像像点坐标,从而提取SAR高程控制点。采用中国登封市、日本横须贺市两个区域的ATLAS数据进行了高分三号SAR高程控制点提取实验,利用提取的高程控制点进行SAR影像几何参数精化,大幅提升了立体定位精度,验证了该文高程控制点提取方法的可行性和有效性。      

Epipolar line estimation and rectification for stereo image pairs

The assumption that epipolar lines are parallel to image scan lines is made in many algorithms for stereo analysis. If valid, it enables the search for corresponding image features to be confined to one dimension and, hence, simplified. An algorithm that generates a vertically aligned stereo pair by warped resampling is described. The method uses grey scale image matching between the components of the stereo pair but confined to feature points.     

Human visual system and segment-based disparity estimation

In this paper, an efficient segment-based disparity estimation algorithm is proposed, based on wavelet transform and human visual system. The core idea is to estimate disparity not only from the left and right images but also from their decomposed sub-bands up to a certain level. The stereo image pair is divided into the segments of homogeneous color. Instead of assigning a disparity value to each pixel inside a segment, a disparity plane is assigned to each segment and the stereo matching problem is formulated as an energy minimization problem in the segmented domain. The optimal disparity plane labeling is approximated by applying belief propagation, which assigns the corresponding disparity plane to each segment. The obtained disparity maps are merged into a single disparity map using the human visual system model. Experiments with stereo image pairs show the validity of the proposed method.     

基于多尺度分析的快速相位立体匹配

基于相位的立体匹配是双目投影光栅相位法中的重要步骤,但传统的相位匹配方法在处理高分辨率图像时因存储空间大大增加,难以达到匹配速度与精度的平衡。文章提出了一种基于多尺度分析的快速相位立体匹配算法,采用分层匹配的策略,对预处理后的左右绝对相位图进行降采样以生成图像金字塔,利用低分辨率的视差匹配结果以预测下一层视差,以此降低下层高分辨率图像的视差搜索范围,达到匹配速度与精度的平衡。实验结果表明,所提算法在保证精度的情况下能有效提升相位立体匹配速度,实现高分辨率相位图快速准确的立体匹配。     

Simple stereo algorithm for 3D positioning of object points

A simple stereo algorithm for 3D positioning of object points is presented. The superimposed difference image is formed from a pair of stereo images. The features are extracted from only the superimposed difference image and the disparity is determined by searching paired features in the given window without recourse to the stereo matching     

融合梯度特性与置信度的立体匹配算法

针对现有局部立体匹配算法在计算匹配代价时, 不能很好区分强弱纹理区域,及在视差计算过程 中,不能很好的解决视差歧义问题,提出一种融合梯度特性与置信度的立体匹配算法。首先 计算梯度特 征,并根据梯度特征信息选择匹配代价计算的匹配窗口,针对强弱不同纹理区域选择不同尺 寸的匹配窗 口,有效的提高了立体匹配精度,降低了误匹配率;然后在视差计算中引入置信度约束条件 ,解决了视差 计算中视差歧义的问题,提高了立体匹配算法的稳定性与精度;最后使用水平与垂直方向交 叉区域检测进 行奇异值的修正。实验结果表明,该算法在Middlebury数据集中31对 立体图像对的平均误匹配率为7.96%,有效的提高了立体匹配精度。     

Information permeability for stereo matching

A novel local stereo matching algorithm is introduced to address the fundamental challenge of stereo algorithms, accuracy and computational complexity dilemma. The time consuming intensity dependent aggregation procedure of local methods is improved in terms of both speed and precision. Providing connected 2D support regions, the proposed approach exploits a new paradigm, namely separable successive weighted summation (SWS) among horizontal and vertical directions enabling constant operational complexity. The weights are determined by four-neighborhood intensity similarity of pixels and utilized to model the information transfer rate, permeability, towards the corresponding direction. The same procedure is also utilized to diffuse information through overlapped pixels during occlusion handling after detecting unreliable disparity assignments. Successive weighted summation adaptively cumulates the support data based on local characteristics, enabling disparity maps to preserve object boundaries and depth discontinuities. According to the experimental results on Middlebury stereo benchmark, the proposed method is one of the most effective local stereo algorithm providing high quality disparity models by unifying constant time filtering and weighted aggregation. Hence, the proposed algorithm provides a competitive alternative for various local methods in terms of achieving precise and consistent disparity maps from stereo video within fast execution time.     

基于多任务学习的立体匹配算法

引入辅助任务信息有助于立体匹配模型理解相关知识,但也会增加模型训练的复杂度。为解决模型训练对额外标签数据的依赖问题,提出了一种利用双目图像的自相关性进行多任务学习的立体匹配算法。该算法在多层级渐进细化过程中引入了边缘和特征一致性信息,并采用循环迭代的方式更新视差图。根据双目图像中视差的局部平滑性和左右特征一致性构建了损失函数,在不依赖额外标签数据的情况下就可以引导模型学习边缘和特征一致性信息。提出了一种尺度注意的空间金字塔池化,使模型能够根据局部图像特征来确定不同区域中不同尺度特征的重要性。实验结果表明:辅助任务的引入提高了视差图精度,为视差图的可信区域提供了重要依据,在无监督学习中可用于确定单视角可见区域;在KITTI2015测试集上,所提算法的精度和运行效率均具有一定的竞争力。     

基于Tao 立体匹配框架的全局优化算法

传统的基于全局优化的立体匹配算法计算复杂度较高,在遮挡和视差不连续区域具有较差的匹配精度。提出了基于Tao 立体匹配框架的全局优化算法。首先采用高效的局部算法获取初始匹配视差;然后对得到的视差值进行可信度检测,利用可信像素点和视差平面假设使用具有鲁棒性的低复杂度算法修正不可信任像素视差值;最后改进置信度传播算法,使其能够自适应地停止收敛节点的消息传播,并对经修正的初始匹配进行优化,提高弱纹理区域匹配准确度。实验结果表明,文中算法有效地降低整体误匹配率,改善了视差不连续及遮挡区域的匹配精度;同时,降低了算法整体复杂度,兼顾了速度,具有一定的实用性。