从阴影恢复形状的径向基函数反射模型研究

目的 为解决传统阴影恢复形状（SFS）算法由于光源方向初始信息估计不准确,恢复的物体表面过于光滑,3维表面形状误差较大等问题,建立了基于径向基函数神经网络的反射模型,并对传统的神经网络进行了改进。方法 建立的基于径向基函数（SFS）神经网络的从阴影恢复形状反射模型代替了传统方法中采用的理想朗伯体表面反射模型。该模型利用径向基函数优秀的局部映射和函数逼近能力来处理SFS问题,通过网络训练过程中的权值代替物体所受到的初始光源信息,解决了传统算法在进行计算时,必须已知光源参数的限制。在该网络模型中添加自适应学习率算法,加速网络的收敛和训练速度。结果 针对SFS问题处理的两幅经典合成图像以及两幅实际图像进行了实验,实验结果表明,改进后的算法在3维视觉效果和3维形状信息的恢复方面都明显优于传统算法。归一化后的3维高度误差结果相比传统算法缩小了60%以上,而且同时适用合成图像和实际图像;自适应学习率的加入,使得网络的训练速度大大加快,对一幅128×128像素的图像,运算速度提升了50%。结论 本文针对SFS问题建立了基于RBF神经网络的从阴影恢复形状反射模型,利用网络模型中的参数代替SFS问题中的初始光源信息,通过最优化方法求解SFS问题。并针对传统的神经网络固定学习率造成网络收敛速度慢,容易陷入局部极小值的问题,加入了自适应学习率算法。实验结果表明,改进后的算法在处理该SFS问题时表现了优秀的性能,适用范围更广,收敛速度更快。     

基于SFS的方法恢复扫描文件图像

从原装订本上扫描文件页面往往会导致扫描图像扭曲的情况。该文简要先介绍了SFS方法及分类。然后提出从技术的角度看利用SFS重构扫描图像这一问题。在现实环境中扫描图像有如下特征：1）一个靠近的移动光源;2）Lambertian式光反射;3）文件偏斜。然后利用基于去除灰度和去除变形模式的方法来恢复扫描文件图像。用以重构书曲面的图像,恢复扫描图像。     

基于SFS的方法恢复扫描文件图像

从原装订本上扫描文件页面往往会导致扫描图像扭曲的情况。该文简要先介绍了SFS方法及分类。然后提出从技术的角度看利用SFS重构扫描图像这一问题。在现实环境中扫描图像有如下特征:1)一个靠近的移动光源;2)Lambertian式光反射;3)文件偏斜。然后利用基于去除灰度和去除变形模式的方法来恢复扫描文件图像。用以重构书曲面的图像,恢复扫描图像。     

基于灰度图像的三维曲面重建系统设计

由二维图像重建三维模型是计算机科学中的一个研究热点。对该问题进行了深入研究，提出了一个基于Shape From Shading（SFS，基于阴影恢复形状）方法进行曲面重建的方法。该方法从图像人手，采用图像处理技术对图像进行必要的处理，由图像的亮度进行曲面三维形状的重建，并利用OpenGL和Visual C＋＋开发了一个三维曲面重建系统，可以由曲面的二维灰度图像方便地重建出其三维形状。该系统的设计对实现产品的快速开发具有重要的意义。     

三维表面重构过程参数的估计研究

在SFS(基于阴影的三维表面重构)各种算法中,都需要光源方向及曲面反射率。这些参数与图像的恢复效果息息相关。针对这些参数,也应运而生了各种各样的行之有效的方法。论文讨论了两种有效的算法,利用合成图像分别进行试验,并对其优缺点和运行效率进行比较,从而为进一步的SFS算法研究提供有价值的参考。     

基于灰度图像的三维曲面重建系统设计

由二维图像重建三维模型是计算机科学中的一个研究热点。对该问题进行了深入研究,提出了一个基于ShapeFrom Shading(SFS,基于阴影恢复形状)方法进行曲面重建的方法。该方法从图像入手,采用图像处理技术对图像进行必要的处理,由图像的亮度进行曲面三维形状的重建,并利用OpenGL和Visual C 开发了一个三维曲面重建系统,可以由曲面的二维灰度图像方便地重建出其三维形状。该系统的设计对实现产品的快速开发具有重要的意义。     

基于阴影的三维表面重构技术的概述

三维表面重构是计算机视觉的主要任务之一。已经发展了各种各样的重构技术,其中利用单幅图像中物体表面明暗变化来恢复其表面形状的技术尤其引人注目,这不仅因为该技术简单易于实现,更重要的是它适用于各种其它方法难以应用的场合,例如,在机载、星载、弹载环境中的利用。论文从SFS问题的研究背景出发,介绍并分析这方面的一些重要进展,通过对各种重构方法的分析与比较,提出SFS问题的研究发展趋势和一些值得研究的方向。     

基于神经网络的三维重建

从明暗恢复形状(shapefromshading,即SFS)是计算机视觉研究领域的一个热门话题。SFS利用图像中明暗变化与物体平面特征的对应关系来恢复物体表面特征。传统方法有估计光源方向,引入梯度光滑约束等方法,但传统的方法存在误差大,重建后物体表面过于光滑等问题,不适合表面起伏大的电镜图像的重建。本文提出以高度z连续作为约束条件,利用神经网络对单幅电镜图像进行重建的算法,并在实验中取得很好的重建效果。     

2SFS方法及其与立体视觉方法的集成方案综述

立体视觉（Stereo Vision）方法是目前利用图象数据获取物体三维信息的主要方法之一。但该方法在图象灰度变化较缓慢的区域，由于难以准确地进行图象间的象素配对．而严重影响了它的效果。利用从明暗重构物体三维表面形状（Shape from Shading，简称SFS）的方法与该方法相结合，是改善重构结果的主要途径之一。文章通过分析SFS问题本身的不适定性，揭示了目前几类主要的SFS算法在可靠性、稳定性、局限性以及实用性方面所存在的问题，并在此基础上，简要地介绍了四类SFS与立体视觉方法相结合的形式．说明了通过利用立体视觉为SFS补充辅助的信息来消除SFS问题的不适定性，并对过去SFs的实现方法进行有效的改进．它是提高集成系统准确性的关键。     

不规则形状图像曲率的自适应计算方法

提出一种针对不规则多形变红血球图像的自适应曲面拟合并计算曲率的方法,通过阴影恢复技术重构细胞表面的高度场形状,利用三维数据点根据最小二乘法进行曲面拟合,选定深度均方误差阈值来决定参与拟合的邻域点.计算得到的高斯曲率、平均曲率可用采表征某一点的表面类型,主曲率则用来观察曲面变化较大的区域.实验结果表明,该方法具有很强的可行性与实用性.     

Optimal Algorithm for Shape from Shading and Path Planning

An optimal algorithm for the reconstruction of a surface from its shading image is presented. The algorithm solves the 3D reconstruction from a single shading image problem. The shading image is treated as a penalty function and the height of the reconstructed surface is a weighted distance. A consistent numerical scheme based on Sethian's fast marching method is used to compute the reconstructed surface. The surface is a viscosity solution of an Eikonal equation for the vertical light source case. For the oblique light source case, the reconstructed surface is the viscosity solution to a different partial differential equation. A modification of the fast marching method yields a numerically consistent, computationally optimal, and practically fast algorithm for the classical shape from shading problem. Next, the fast marching method coupled with a back tracking via gradient descent along the reconstructed surface is shown to solve the path planning problem in robot navigation.     

Shape from Shading with Interreflections Under a Proximal Light Source: Distortion-Free Copying of an Unfolded Book

We address the problem of recovering the 3D shape of an unfolded book surface from the shading information in a scanner image. This shape-from-shading problem in a real world environment is made difficult by a proximal, moving light source, interreflections, specular reflections, and a nonuniform albedo distribution. Taking all these factors into account, we formulate the problem as an iterative, non-linear optimization problem. Piecewise polynomial models of the 3D shape and albedo distribution are introduced to efficiently and stably compute the shape in practice. Finally, we propose a method to restore the distorted scanner image based on the reconstructed 3D shape. The image restoration experiments for real book surfaces demonstrate that much of the geometric and photometric distortions are removed by our method.     

Appearance Harmonization for Single Image Shadow Removal

Shadow removal is a challenging problem and previous approaches often produce de‐shadowed regions that are visually inconsistent with the rest of the image. We propose an automatic shadow region harmonization approach that makes the appearance of a de‐shadowed region (produced using any previous technique) compatible with the rest of the image. We use a shadow‐guided patch‐based image synthesis approach that reconstructs the shadow region using patches sampled from non‐shadowed regions. This result is then refined based on the reconstruction confidence to handle unique textures. Qualitative comparisons over a wide range of images, and a quantitative evaluation on a benchmark dataset show that our technique significantly improves upon the state‐of‐the‐art.     

物体三维形状恢复的遗传算法方法

提出了一种新的物体三维形状恢复的遗传算法方法。用固定位置的摄像机在不同位置的球扩展光源下获取图象序列,并用遗传算法对物体表面每一点的法线矢量进行快速搜索。实验结果表明,此方法能有效地恢复扩展光源下物体的三维形状。不仅放宽了对光源和物体表面的限制,而且精度及鲁棒性均有很大提高。     

基于照明参数与反射系数的分层SFS算法

提出一种由明暗信息复原形状的鲁棒算法.此算法能有效地估计照明方向、漫反射 系数、照明天顶角以及沿图像轮廓由明暗信息复原形状,并且在考虑自阴影影响情况下,用新 方法从图像的统计特征估计照明的仰角和表面反射系数,使重建强度梯度接近输入图像梯度 实现平滑约束.该方法为数据驱动,稳定可靠,能同时更新表面斜率与高度图,大大减小发射 项与可积分项内的剩余误差.最后给出SFS(Shape from Shading)算法的分层实现.     

利用形体特征的铅笔素描画生成

铅笔素描是以单色线条来表现物体的艺术。画家观察物体的形体结构,以线塑型表现物体明暗层次和形体特征。为了表现物体的立体感,提出一种利用形体特征的铅笔素描画生成方法。首先对图像进行双边滤波处理,去除图像微小细节;然后由亮度图像计算其向量场,根据物体的形体特征对向量进行平滑,使其符合原图像的形体特征;最后利用线积分卷积的方法生成铅笔素描纹理,调整明暗对比后得到铅笔素描的效果。实验结果表明,该方法能有效地绘制铅笔素描的立体感和明暗关系。     

Efficient,complete radiosity ray tracing using a shadow-coherence method

Most two-pass rendering methods calculate a radiosity shading for each patch or element in a scene in the first pass. This shading contains two components: one for the light received directly from the main light sources and one representing the intensity of the light received indirectly by means of diffuse and specular interreflection between patches. However, it is very difficult to achieve accurate representation of the distribution of this radiosity shading over the patch, particularly where clearly visible shadow boundaries exist. A better approach is to store only the indirect reflection component in the form of radiosity shading, and to calculate the direct reflection component during the second pass by casting shadow rays. This approach normally requires that many shadow rays must be cast. However, the number of rays for shadow testing can be kept low by selecting only those light sources that substantially contribute to the shading of a patch and applying an adaptive image refinement technique in combination with a shadow coherence method.     

一种基于二维图像的三维仿真方法研究

针对二维的图像数据,综合运用计算机视觉、计算机图像处理和计算机辅助几何设计理论与技术,提出了一种实用的三维仿真方法.采用阴影恢复形状的方法获取三维形貌信息,利用图像分割技术提取物体的二维轮廓信息,通过三维形貌信息与二维轮廓信息的融合技术建立物体的数字化模型,通过B样条的万法实现数字化模型的重构.实例表明,方法可行有效,能够有效地去除图像的背景信息,改善重构模型的分辨力,为基于二维图像的三维仿真技术的广泛应用提供了条件.     

Editing Soft Shadows in a Digital Photograph

In this article, we develop tools for shadow modification in images where a shadowed region is characterized by soft boundaries with varying sharpness along the shadow edges. Modeling shadow edges presents an interesting challenge because they can vary from infinitely sharp edges for shadows produced by a point light source to extremely soft edges for shadows produced by large area light sources. We propose an entirely image-based shadow editing tool for a single-input image. This technique for modeling, editing, and rendering shadow edges in a photograph or a synthetic image lets users separate the shadow from the rest of the image and make arbitrary adjustments to its position, sharpness, and intensity. These machine-adjustable photographs can offer interactivity that might improve images' expressiveness and help us investigate the influence of boundary sharpness on the perception of object-to-object contact, as well as understand how humans assess shadows to estimate object height above a ground plane     

Estimating ground fractional vegetation cover using the double-exposure method

Fractional vegetation cover (FVC) is a key parameter in ecological models. It is important to determine the ground FVC quickly and accurately in studies of soil erosion, surface energy balance, and carbon cycling. As one of the FVC ground measurement methods, the photographic method is easy to operate with relatively high precision. However, its classification result showed poor accuracy when an image of a high-contrast scene contained a shadow region where a low signal-to-noise ratio (SNR) existed, because the single-exposure image in the photographic method did not contain sufficient surface information about both the illuminated and shadowed parts. This article presents application of a double-exposure photographic method to determine vegetation cover in the shadow region of an image. It consists of two measurements used in acquiring images (normal and over-exposure) and one image-processing part to handle the obtained images. Illuminated vegetation and soil, as well as the shadow region, was classified with the normally exposed image in the intensity, hue, and saturation (IHS) colour space, and the shadow region was further classified as shadowed vegetation and shadowed soil using the over-exposed image. The results indicate that the over-exposed image reduced the average bias of the FVC in the shadow region from 15.40% to ?4.14% and the root mean square error (RMSE) from 0.174 to 0.066. The RMSE of the entire scene was 0.055 in the over-exposed image and 0.092 in the single-exposed image. The double-exposure method also showed a better classification result than the high dynamic range method in deep shadow regions. This study shows that this method is capable of distinguishing vegetation and soil in the shadow region and thus it is an effective and accurate method for ground FVC measurement.