全局光照环境中的逆向绘制

提出一种恢复场景中所有物体的反射特性的方法.算法以一个全景图、场景的完整几何模型和光源信息为输入,结果是场景的一个完整反射模型.恢复是以逐步求精的方式进行的.先假定物体表面是漫反射面并生成一幅全景图,然后算法逐步迭代,比较绘制的全景图和原始全景图,如果有的物体的误差超过某个阈值,算法为他们选择更负责的反射模型.最后,场景中的每个物体有了一个合适的反射模型,可以在新的光照和视点条件下绘制,旧的物体可以从场景中移去,新的物体可以添加到场景中.对漫反射、各向同性反射和各向异性反射纹理面的纹理恢复也作了深入研究;高光和阴影的影响也能基本去除.     

一种真实物体表面反射属性采集与建模方法

为了快速获取物体表面反射属性数据和三维几何数据,研制了一套包括相机、光源、三维扫描仪、控制系统等的物体表面反射属性数据采集系统,在此基础上,提出一种单材质物体表面反射属性建模方法.该方法根据物体反射特性对漫反射与镜面反射分别建模,能够逼真地构造出物体表面反射属性模型,并且保证了参数求解的稳定性.最后设计并实现了反射属性模型编辑工具.实验结果表明,利用该编辑工具可以实时、可视地调整模型参数,从而满足用户对反射属性模型编辑的需求.     

基于SFS方法的三维重构及精度分析

从明暗恢复形状(SFS)是计算机视觉中三维重构问题的研究热点和难点之一,目前已有算法存在两个问题:1)选择的反射模型不符合物体表面的反射特性;2)引入的约束条件和求解过程过于复杂,求解速度慢,效率低。对SFS算法进行了详细分析,引入了朗伯特光照反射模型,对物体表面做球形假设,然后对图像做近似微分运算以求出高度函数,实现了利用单幅灰度图像恢复物体表面三维形状并仿真的数据处理方法,同时对传统线性化SFS算法和所提算法进行了实验验证,对两种模型的重构精度和算法的执行效率进行了比较和分析。实验仿真结果表明,在保证一定精度的前提下,所提算法的执行效率比传统算法高。     

基于最佳漫反射像素的汽车表面高光检测

汽车表面常常反射出表征光源颜色的高光,高光的颜色严重影响了汽车的真实颜色.因此在识别汽车颜色之前需要将汽车表而的高光像素检测出来,以提高颜色识别的准确率.结合原图像和对应的无高光图像提出了最佳漫反射像素的概念,并以最佳漫反射像素为基础提出了一种检测单张彩色图像中汽车表面高光的算法.算法简单、容易实现,其理论基础是二分光反射模型.实验结果表明算法有效、运算速度快,可以满足汽车颜色识别系统准确性和实时性的要求.     

融合Swin-Transformer网络模型的水体高光区域提取

在强光的照射下，水体的镜面反射往往会对遥感影像产生很大影响，其主要表现就是在图像上产生大小不同、形状各异的亮斑。这些亮斑附近的地物信息基本上都被淹没，对后期的影像分析会造成不同程度的影响，因此对这些亮斑的检测识别就显得尤为重要。文章以DeeplabV3plus为主要网络，提出一种融合Swin-Transformer模块的网络模型。该模型将Swin-Transformer网络作为一个模块与卷积骨干网络并行提取特征。提取出的两类特征经上采样后进行特征融合，再经多次卷积等实现了水体亮斑的识别与分割。实验结果表明，该模型能够对不同类型、不同形状的水体亮斑进行识别分割，其平均交并比为93.44%。     

基于双色反射模型的彩色结构光颜色识别的研究

为了快速准确地识别出彩色结构光系统中的投射光颜色信息,该文提出了基于双色反射模型的投射光颜色识别算法.首先通过对数码相机和投影设备进行色度标定,以消除两者之间的耦合性差异;接着通过估计物体三颜色通道光谱反射率以及分离镜面反射成分和漫反射成分,来修正物体本身颜色和镜面反射对投射光源颜色的影响.实验结果表明,该文提出的投射光颜色识别算法对于双色反射模型条件下的彩色结构光颜色识别具有鲁棒性高、计算速度快、识别准确度高等优点.     

基于粗糙表面模型的三维形貌恢复研究

文中提出了一种针对粗糙物体的表面反射模型,即用Oren-Nayar模型代替通用的朗伯体表面反射模型(Lamber-tian surface reflection model),并基于透视投影从明暗恢复形状(shape from shading),对图像进行三维重建,此三维重建具有很高的现实意义.实验用该模型对两幅较粗糙的真实图像进行重建并与在朗伯体模型下得到的结果进行比较,实验结果表明对于粗糙物体文中方法能得到较好的恢复效果,说明本SFS方法是有效且收敛的.     

从单幅高动态范围图像恢复环境中物体的材质

提出一种从单幅高动态范围图像恢复一般环境中物体材质的方法,适用于单一材质物体,对物体形状和光照条件没有任何特殊要求.在一般光照环境中,获取被考察物体的一幅高动态范围图像以及用来近似物体光照的一个或几个高动态范围环境映照,然后用模拟退火算法求解逆向绘制问题.在求解过程中采用了基于图像的光照和光线跟踪技术,充分考虑了物体自身互反射的影响.最后得到了物体表面反射模型的最优参数.若与基于图像的建模技术相结合,可以根据真实物体的照片建立真实感模型.     

基于物理模型的彩色图象理解算法

本文给出一个彩色图象理解算法。算法首先对图象上的颜色变化(由光照和物体颜色引起)进行分析与综合,然后分割图象。算法的基础是双色反射模型理论,理论认为反射光的颜色是界面反射(耀斑颜色)和本体反射(物体颜色)的线性组合,这两种反射光在颜色空间的三维直方图中形成特定的聚类(点簇)。因此分析聚类的性质可帮助确定光照和物体的颜色,但是有意义的聚类的生成又以图象中物体区域的确定为前提。算法按照假设检验的策略,依据图象中的连通性和颜色空间中聚类的特征,完成彩色图象的分割,并产生对景物中所发生的光学过程的物理描述。该描述包括本征反射图象,分割图象,物体和光照颜色的符号描述。本征反射图象包括只反映界面反射的耀斑图象和从原图象中去除耀斑影响后的本体图象。     

一种精确的光照模型

在太阳光照射下，不同物体呈现出不同颜色，原因就在于物体对光谱成分有选择吸收和选择反射的性质。本文在在分析现有模型存在问题的基础上，提出了一种综合的能更逼真地模拟各光照效果的光照模型。     

基于物理模型的彩色图像分割

本文给出一个基于光学物理模型的真实彩色图像分割算法.算法首先对图像上的颜色变 化(由光照和物体颜色引起)进行分析与综合,然后分割图像.算法的基础是双色反射模型理 论,该理论认为反射光的颜色是界面反射(耀斑颜色)和本体反射(物体颜色)的线性组合,这两 种反射光在颜色空间的三维直方图中形成特定的聚类(点簇).因此分析聚类的性质可帮助确 定光照和物体的颜色,但是有意义的聚类的生成又以图像中物体区域的确定为前提.算法按 照假设检验的策略,依据图像中的连通性和颜色空间中聚类的特征,完成彩色图像的分割,并 产生对景物中所发生的光学过程的物理描述.该描述包括本征反射图像、分割图像、物体和光 照颜色的符号描述.本征反射图像包括只反映界面反射的耀斑图像和从原图像中去除耀斑影 响后的本体图像.     

Analysis of colour channel coupling from a physics-based viewpoint: Application to colour edge detection

The Dichromatic Reflection Model (DRM) introduced by Shafer in 1985 is surely the most referenced physics-based model of image formation. A preliminary analysis of this model derives in the conclusion that colour channels remain coupled by the reflectance of objects surface material. Taking this observation as a basis, this paper shows that this coupling manifests itself at the signal level in the form of a set of properties only satisfied in uniform reflectance areas. Such properties are deeply analysed and formalized throughout the paper, and, eventually, they are stated geometrically. As will be seen, a compatibility relationship stems from this geometric interpretation, which allows checking at a very low cost whether two pixels correspond to the same scene reflectance or not. Finally, an edge detector based on the use of the previous relationship is presented as an example of application. This edge detector inherits all the properties of the compatibility relationship: simplicity, low computational power requirements, sensor noise adaptivity and insensitivity to image intensity changes due to scene objects curvature.     

Linear color segmentation and its implementation

A framework for color image segmentation is presented, which combines color histogram analysis and region merging approach. Its main goal is to segment an image at material boundaries (i.e., discontinuities of reflectance properties) while ignoring spatial color inhomogeneities of uniformly pigmented (colored) objects, caused by accidents of illumination and viewing geometry. Theoretical examination of light spectrum transformations upon light reflection from material surfaces and upon interaction with a sensor system shows that in a wide variety of viewed scenes (even containing interreflections and highlight areas) uniformly pigmented objects are projected to the color space of the sensor as planar, linear, or point-like clusters, depending on lighting and viewing conditions and object geometry. To detect such clusters in the color space, three methods are suggested: Generalized Hough Transform method, gradient descent method, and eigenvectors method. A framework algorithm of color segmentation based on region merging approach is developed, which can use any of these methods. Testing this algorithm with both artificially generated and real images shows quite reliable results.     

一体式中医舌象采集分析系统设计

舌象采集是中医舌象分析中非常重要的一环,一套稳定、可靠、高精度的舌象采集系统直接影响到舌象分析和病情诊断的准确性。针对上述要求,设计了一种一体式的中医舌象采集分析系统,具有结构简单,功能全面,体积小等特点。通过积分球搭建的光照环境保证了舌体的受光均匀。使用MFC编写采集处理程序,便于升级维护。研究了一种手动调节相机白平衡参数的方法,保证采集过程中舌象颜色的准确性。     

高光去除的聚类算法改进

高光去除是计算机视觉领域研究的一个热点问题.现有的基于双色反色模型分离漫反射分量和镜面反射分量去除单幅图像中的高光的方法,容易引起图像颜色失真和纹理的丢失.针对此问题,在使用像素强度比去高光的基础上改进了像素聚类算法,能够更准确的进行像素分类,改善图像颜色失真的现象.首先计算原图像与最小强度值单通道图像的差值得到无高光图像.然后根据无高光图像计算与高光区域相关的每个像素点的最大漫反射色度值和最小漫反射色度值.最后将高光区域内的像素点转换到最小最大色度空间,对高光区域内的像素点进行xmeans聚类,利用分类后漫反射像素点的强度比估计值很容易分离高光区域像素点的镜面反射分量,从而得到去高光图像.实验结果表明,与现有的方法对比,峰值信噪比值平均提升了2%至4%,图像颜色失真和纹理丢失状况得到改善,视觉效果更好.     

The measurement of highlights in color images

In this paper, we present an approach to color image understanding that accounts for color variations due to highlights and shading. We demonstrate that the reflected light from every point on a dielectric object, such as plastic, can be described as a linear combination of the object color and the highlight color. The colors of all light rays reflected from one object then form a planar cluster in the color space. The shape of this cluster is determined by the object and highlight colors and by the object shape and illumination geometry. We present a method that exploits the difference between object color and highlight color to separate the color of every pixel into a matte component and a highlight component. This generates two intrinsic images, one showing the scene without highlights, and the other one showing only the highlights. The intrinsic images may be a useful tool for a variety of algorithms in computer vision, such as stereo vision, motion analysis, shape from shading, and shape from highlights. Our method combines the analysis of matte and highlight reflection with a sensor model that accounts for camera limitations. This enables us to successfully run our algorithm on real images taken in a laboratory setting. We show and discuss the results.This material is based upon work supported by the National Science Foundation under Grant DCR-8419990 and by the Defense Advanced Research Projects Agency (DOD), ARPA Order No. 4976, monitored by the Air Force Avionics Laboratory under contract F33615-84-K-1520. Any opinions, findings, and conclusions or recommendations expressed in this publication are those of the authors and do not necessarily reflect the views of the National Science Foundation, the Defense Advanced Research Projects Agency, or the US Government.     

基于快速双边滤波的图像高光去除研究

在各向异性的物体中,高光被视为是漫反射分量以及镜面反射分量的一种线性组合。单幅图像的高光去除是计算机视觉中一项非常有挑战性的课题。很多方法试图将漫反射分量、镜面反射分量进行分离,然而这些方法往往需要图像分割等预处理过程,方法鲁棒性较差且比较耗时。基于双边滤波器设计了一种高效的高光消除方法,该方法利用最大漫反射色度存在着局部平滑这一性质,使用双边滤波器对色度的最大取值进行传播与扩散,从而完成整幅图像高光去除。方法采用一种加速策略对双边滤波器进行速度优化,与目前流行的方法相比,有效提升了方法的执行效率。与传统方法相比,该方法高光去除效果更好,处理速度更快,非常适用于一些实时应用的场合。     

Linked multi-component mobile robots: Modeling,simulation and control

The Linked Multi-Component Robotic Systems (L-MCRS) consists of a group of mobile robots carrying a passive uni-dimensional object (a hose or a wire). It is a recently identified unexplored and unexploited category of multi-robot systems. In this paper we report the first effort on the modeling, control and visual servoing of L-MCRS. Modeling has been tackled from geometrical and dynamical points of view. The passive element is modeled by splines, and the dynamical modeling is achieved by the appropriate extension of Geometrically Exact Dynamic Splines (GEDS). The system’s modeling allows realistic simulation, which can be used as a test bed for the evaluation of control strategies. In this paper we evaluate two such control strategies: a baseline global controller, and a fuzzy local controller based on the observation of the hose segment between two robots. Finally, we have performed physical experiments on a team of robots carrying a wire under a visual servoing scheme that provides the perceptual information about the hose for the fuzzy local controller. Visual servoing robust image segmentation is grounded in the Dichromatic Reflection Model (DRM).