大场景的视频全景图拼接

为了解决大场景全景图拼接过程中的误差累积问题,提高图像拼接的一致性,提出了一个新的全景图拼接算法。把全局图像配准看作是一个统计估计问题,运用增广的卡尔曼滤波对图像的全局变换参数进行递归地增广和估计。实验结果表明,得到的变换参数是全局一致的,生成的全景图不存在拼接裂缝。拼接算法考虑了各种不确定性,适用于噪声大场景的全景图拼接。     

A New Method of Image Mosaicking and Its Application to Cultural Heritage Representation

This paper presents an original two-step procedure for estimating projective transformations between pairs of images: first, the transformation between the images is approximated as an affine transformation; second, this estimate is refined into that of a projective transformation. This strategy for matching projective views is computationally very efficient. The proposed method can be applied both to mosaicking of high resolution images of planar textured objects (e.g., frescoes and paintings), with subpixel accuracy, and to construction of panoramic images. Practical examples of mosaicking of cultural heritage imagery obtained by using the presented procedure are discussed in the paper.     

视频图像序列运动参数估计与动态拼接

本文采用多重分层叠代算法来估计全局运动参数，并提出应用于动态拼接的运动分割新方法，实现既有摄像机运动又有物体运动的视频图像序列自动拼接。我们的方法基本步骤如下：首先进行全局运动参数的初始估计，并且在分层叠代过程中进行区域分类，得到初始运动模板。接着空间分割原始图像，先根据图像的空间属性由底向上分层合并图像空间区域，再利用视频图像时间属性进一步向上合并，得到图像空间分割结果。然后结合初始运动模板和图像空间分割结果，采用区域分类新方法重新对图像空间分割结果的每个区域进行分类。然后根据分类结果逐步精确求解全局运动参数。最后进行图像合成，得到全景拼接图像。我们的方法利用了多重分层叠代的优点，并且充分考虑到视频图像空间和时间上的属性，实现了运动物体和覆盖背景的精确分割，避免了遮挡问题对全局运动参数估计精度的影响。而且在图像合成时我们解决了拼接图可能产生模糊或某些区域不连续等问题。实验结果表明我们的方法实现了动态视频图像序列高质量的全景拼接。     

宽基线视差图像的拼接算法

针对两幅视差图像的拼接问题,提出了一种新算法,即利用Hessian仿射不变检测算子检测出特征区域,利用SIFT特征描述算子提取特征区域特征矢量,根据特征矢量的欧几里德距离来建立图像间的稀疏对应关系;由这些对应点稀疏地确定场景中的一些点,以这些点为顶点建立场景的三角面片近似,再据此将重叠区域重投影生成推扫式成像的中间部分图像。将中间部分推扫式成像图像和原左图像的左半部分以及原右图像的右半部分一起拼接生成大图像。利用实际图像进行的拼接实验表明该算法是一个有效的视差图像拼接算法。     

Fingerprint image mosaicking by recursive ridge mapping.

To obtain a large fingerprint image from several small partial images, mosaicking of fingerprint images has been recently researched. However, existing approaches cannot provide accurate transformations for mosaics when it comes to aligning images because of the plastic distortion that may occur due to the nonuniform contact between a finger and a sensor or the deficiency of the correspondences in the images. In this paper, we propose a new scheme for mosaicking fingerprint images, which iteratively matches ridges to overcome the deficiency of the correspondences and compensates for the amount of plastic distortion between two partial images by using a thin-plate spline model. The proposed method also effectively eliminates erroneous correspondences and decides how well the transformation is estimated by calculating the registration error with a normalized distance map. The proposed method consists of three phases: feature extraction, transform estimation, and mosaicking. Transform is initially estimated with matched minutia and the ridges attached to them. Unpaired ridges in the overlapping area between two images are iteratively matched by minimizing the registration error, which consists of the ridge matching error and the inverse consistency error. During the estimation, erroneous correspondences are eliminated by considering the geometric relationship between the correspondences and checking if the registration error is minimized or not. In our experiments, the proposed method was compared with three existing methods in terms of registration accuracy, image quality, minutia extraction rate, processing time, reject to fuse rate, and verification performance. The average registration error of the proposed method was less than three pixels, and the maximum error was not more than seven pixels. In a verification test, the equal error rate was reduced from 10% to 2.7% when five images were combined by our proposed method. The proposed method was superior to other compared methods in terms of registration accuracy, image quality, minutia extraction rate, and verification.     

Systems and Experiment Paper: Construction of Panoramic Image Mosaics with Global and Local Alignment

This paper presents a complete system for constructing panoramic image mosaics from sequences of images. Our mosaic representation associates a transformation matrix with each input image, rather than explicitly projecting all of the images onto a common surface (e.g., a cylinder). In particular, to construct a full view panorama, we introduce a rotational mosaic representation that associates a rotation matrix (and optionally a focal length) with each input image. A patch-based alignment algorithm is developed to quickly align two images given motion models. Techniques for estimating and refining camera focal lengths are also presented.In order to reduce accumulated registration errors, we apply global alignment (block adjustment) to the whole sequence of images, which results in an optimally registered image mosaic. To compensate for small amounts of motion parallax introduced by translations of the camera and other unmodeled distortions, we use a local alignment (deghosting) technique which warps each image based on the results of pairwise local image registrations. By combining both global and local alignment, we significantly improve the quality of our image mosaics, thereby enabling the creation of full view panoramic mosaics with hand-held cameras.We also present an inverse texture mapping algorithm for efficiently extracting environment maps from our panoramic image mosaics. By mapping the mosaic onto an arbitrary texture-mapped polyhedron surrounding the origin, we can explore the virtual environment using standard 3D graphics viewers and hardware without requiring special-purpose players.An erratum to this article can be found at     

采用分段插值的球状全景图自动拼接方法

目前,能够覆盖所有视觉范围的球状全景图拼接方法较少,而且存在着一定的缺陷,例如迭代优化算法的不稳定性,图像采集设备的特殊性。为了解决这些问题,提出了一种自动的球状全景图拼接方法,它只需使用普通设备进行图像采集。该方法首先采用基于傅立叶变换的相位相关算法近似求解图像之间的变换关系。在拼接过程中,为了避免误差积累,首先生成一系列纵向分块图像,然后通过分段插值策略将它们拼接成无缝的球状全景图。通过对多种场景的实验表明,该方法计算效率高,并且能够达到满意的拼接效果。     

Empirical correction of multiple flightline hyperspectral aerial image mosaics

Aerial survey provides the user with great flexibility in terms of the geometry of sensing and the timing of measurements, but mosaicking individual aerial images to produce an extensive coverage remains a problem. Empirical methods based on normalising individual images to a common standard are used widely to create visually acceptable mosaics. However, the effect of these methods on quantitative estimation of land surface properties is unknown. An existing method for atmospherically correcting an aerial image mosaic involves fitting a regression model using pixels from the overlapping edges of adjacent flightlines. Here, we demonstrate a new method of atmospherically correcting an aerial image mosaic, based on use of an additional orthogonal flightline. The two methods were compared by using the two image mosaics to calculate vegetation indices (NDVI, SAVI, ARVI), which were then used to predict leaf area index, which was known in detail from ground survey. The second method was found to have lower uncertainty for all three vegetation indices tested. ARVI was found to be the most robust of the three when applied across multiple flightlines, regardless of the method of atmospheric correction.     

Image shadow removal using pulse coupled neural network

This paper introduces an approach for image shadow removal by using pulse coupled neural network (PCNN), based on the phenomena of synchronous pulse bursts in the animal visual cortexes. Two shadow-removing criteria are proposed. These two criteria decide how to choose the optimal parameter (the linking strength /spl beta/). The computer simulation results of shadow removal based on PCNN show that if these two criteria are satisfied, shadows are removed completely and the shadow-removed images are almost as the same as the original nonshadowed images. The shadow removal results are independent of changes of intensities of shadows in some range and variations of the places of shadows. When the first criterion is satisfied, even if the second criterion is not satisfied, as to natural grey images that have abundant grey levels, shadows also can be removed and PCNN shadow-removed images retain the shapes of the objects in original images. These two criteria also can be used for color images by dividing a color image into three channels (R, G, B). For shadows varying drastically, such as the noisy points in images, these two criteria are still right, but difficult to satisfy. Therefore, this approach can efficiently remove shadows that do not include the random noise.     

一种用于动态场景的全景表示方法

针对全景图无法表示动态场景这一问题，提出一种用于动态场景的全景图表示方法，将视频纹理和全景图结合起来，构造动态全景图。系统首先将一系列定点拍摄的图像拼接成全景图，然后用摄像机拍摄场景中周期或随机运动的物体，提取视频纹理，最后视频纹理与全景图对准并融合，生成动态全景图。动态全景图既保持静态全景图全视角漫游的优点，又使得场景具有动态的特征，极大地增强漫游的真实感。     

The wonham filter with random parameters: rate of convergence and error bounds

Let /spl alpha/(t) be a finite-state continuous-time Markov chain with generator Q=(q/sup ij/)/spl isin/R/sup m/spl times/m/ and state space M={z/sup i/,...,z/sup m/}, where z/sup 1/ for i/sub /spl middot//spl middot//spl middot//spl middot//m are distinct real numbers. When the state-space and the generator are known a priori, the best estimator of /spl alpha/(t) (in terms of mean square error) under noisy observation is the classical Wonham filter. This note addresses the estimation issue when values of the state-space or values of the generator are unknown a priori. In each case, we propose a (suboptimal) filter and prove its convergence to the desired Wonham filter under simple conditions. Moreover, we obtain the rate of convergence using both the mean square and the higher moment error bounds.     

Graph based construction of textured large field of view mosaics for bladder cancer diagnosis

Large field-of-view panoramic images greatly facilitate bladder cancer diagnosis and follow-up. Such 2D mosaics can be obtained by registering the images of a video-sequence acquired during cystoscopic examinations. The scientific challenge in the registration process lies in the strong inter- and intra-patient texture variability of the images, from which primitives cannot be robustly extracted. State-of-the-art registration methods are not at the same time robust and accurate, especially for image pairs with a small amount of overlap (less than 90%) or strong perspective transformations. Moreover, no previous contribution to cystoscopy mosaicing presents panoramic images created from multiple overlapping sequences (e.g. “zigzags” or loop trajectories). We show how such overlapping sections can be automatically detected and present a novel registration algorithm that robustly superimposes non-consecutive image pairs, which are related by stronger perspective transformations and share less overlap than consecutive images (less than 50%). Globally coherent panoramic images are constructed using a non-linear optimization and a novel contrast-enhancing stitching method. Results on both phantom and patient data are obtained using constant algorithm parameters, which demonstrate the robustness of the proposed method. While the methods presented in this contribution are specifically designed for cystoscopy mosaicing, they can also be applied to more general mosaicing problems. We demonstrate this on a traditional stitching application, where a set of pictures of a building are stitched into a seamless, globally coherent panoramic image.     

一种基于多边形柱面全景图的虚拟漫游新方法

提出了一种基于图像绘制的多边形柱面全景图的虚拟漫游方法。利用普通 的手持相机在一个多边形区域内沿某一路径拍摄并拼接多幅全景图,通过基于SIFT 的特征 点检测来计算深度,用狭缝图像插值来实现整个区域内的平滑漫游。该方法具有采样简单、 虚拟场景真实感强,支持连续大范围漫游的特点。     

遥感彩色影像镶嵌拼接缝的消除方法研究

对遥感影像拼接缝消除方法存在的问题进行了分析,提出了基于色度空间变换和动态宽度的遥感彩色图像拼接缝消除新方法。在HLS色彩空间,从色度、亮度和饱和度三个方面对拼接缝两侧像元值差异进行消除后,再转换为RGB彩色图像,并用4幅彩红外航空遥感图像进行了试验。研究结果表明,所提出的方法对于遥感彩色图像拼接缝消除具有较好的效果,算法简单、易于实现。     

一种360度柱面全景图快速生成算法

全景图像是构造虚拟环境的基本要素之一,本文提出了一种新的360柱面全景图绘制算法。首先对原始图像进行柱面投影,然后通过对图象重叠部分的对应特征区域进行匹配和拼合来实现图象无缝镶嵌。实验表明该算法运算量较小,能有效、快速地生成柱面全景图。     

基于灰关联分析的遥感影像无缝拼接*

根据中心像元与周围像元之间的邻近像元效应,提出了一种基于灰关联分析的多景遥感影像无缝拼接方法。该方法以影像重叠区域中心像元邻域作为参考序列与比较序列,利用斜率关联度计算两者之间的灰关联度,找到一条影像色调和纹理差异较小的拼接线,并对其两侧作加权灰度平滑处理,以消除拼接图像之间因色调差异造成的接缝效应。实验结果表明,该方法算法简单,易于实现,影像拼接质量较好。     

Video mosaics for virtual environments

As computer-based video becomes ubiquitous with the expansion of transmission, storage, and manipulation capabilities, it will offer a rich source of imagery for computer graphics applications. This article looks at one way to use video as a new source of high-resolution, photorealistic imagery for these applications. If you walked through an environment, such as a building interior, and filmed a video sequence of what you saw you could subsequently register and composite the video images together into large mosaics of the scene. In this way, you can achieve an essentially unlimited resolution. Furthermore, since you can acquire the images using any optical technology, you can reconstruct any scene regardless of its range or scale. Video mosaics can be used in many different applications, including the creation of virtual reality environments, computer-game settings, and movie special effects. I present algorithms that align images and composite scenes of increasing complexity-beginning with simple planar scenes and progressing to panoramic scenes and, finally, to scenes with depth variation. I begin with a review of basic imaging equations and conclude with some novel applications of the virtual environments created using the algorithms presented     

Two-axis electromagnetic microscanner for high resolution displays

A novel microelectromechanical systems (MEMS) actuation technique is developed for retinal scanning display and imaging applications allowing effective drive of a two-axes scanning mirror to wide angles at high frequency. Modeling of the device in mechanical and electrical domains, as well as the experimental characterization is described. Full optical scan angles of 65/spl deg/ and 53/spl deg/ are achieved for slow (60 Hz sawtooth) and fast (21.3 kHz sinusoid) scan directions, respectively. In combination with a mirror size of 1.5 mm, a resulting /spl theta//sub opt/D product of 79.5 deg/spl middot/mm for fast axis is obtained. This two-dimensional (2-D) magnetic actuation technique delivers sufficient torque to allow non-resonant operation as low as dc in the slow-scan axis while at the same time allowing one-atmosphere operation even at fast-scan axis frequencies large enough to support SXGA (1280 /spl times/ 1024) resolution scanned beam displays.     

一种改进图像拼接算法的仿真研究

研究图像拼接优化问题,在图像拼接中有精度要求,但由于受到光照、目标移动、视角等影响,图像含有噪声,且容易发生变形,传统Harris特征提取算子不能适应图像变形特性,容易获得很多错误的特征点,导致后继的图像拼接精度低。为了提高图像拼接精度,提出一种改进Harris算子的图像拼接方法。首先对待拼接图像进行平滑和几何校正处理,然后采用改进Harris算子提取图像特征点,最后采用傅立叶变换实现图像配准,平均值法进行图像融合,得到一幅全景图像。仿真结果表明,改进算法不仅减少了图像拼接耗费的时间,同时提高了图像精度和拼接的效率,达到了图像无缝拼接的效果。     

Plastic merge procedure for mosaics of polygons

Graphic input, while providing a congenial medium for the user, can lead to problems of noisy data. In the case of mosaics of arbitrary polygons input graphically, the problem lies in boundary misalignments and the consequent lack of guaranteed common boundaries. A general plastic merge procedure operating on mosaics of arbitrary rectilinear polygons is described which corrects such boundary misalignments. The work was originally motivated by the needs of an applications project funded by sponsors with user interests. With further support from SRC, the underlying concepts were subsequently expanded and are presented here in a form which is not application-specific.