Spherical surface parameterization for perspective shape from shading

We propose a new mathematical formulation for perspective shape from shading (PSFS) problems. Our approach is based on representing the unknown surface as a spherical surface, expressed by Euclidean distance to the optical centre, as opposed to the traditional representation by distance from the image plane. We show that our parameterization is better suited for perspective camera models and results in simpler models and equations for classical PSFS problems with a light source in the optical centre. The unknown distance field satisfies a simple isotropic Eikonal equation on the unit sphere in the case of a Lambertian surface reflection model. This is in contrast to previous methods with depth field parameterization, which result in anisotropic equations. Adding light attenuation to the model, we show that the distance field satisfies an Eikonal type of equation with a zero order term. We show how both Eikonal equations can be approximated by very efficient Fast Marching methods. A number of numerical tests and examples are provided to demonstrate our approach, and to compare with previous work. Our results indicate competitive accuracy and computational time that are several orders of magnitude faster than state-of-the-art iterative algorithms. A preliminary investigation indicates that our method could be used in more general PSFS problems.     

Estimation of illuminant direction, albedo, and shape from shading

A robust approach to the recovery of shape from shading information is presented. Assuming uniform albedo and Lambertian surface for the imaging model, two methods for estimating the azimuth of the illuminant are presented. One is based on local estimates on smooth patches, and the other method uses shading information along image contours. The elevation of the illuminant and surface albedo are estimated from image statistics, taking into consideration the effect of self-shadowing. With the estimated reflectance map parameters, the authors then compute the surface shape using a procedure that implements the smoothness constraint by requiring the gradients of reconstructed density to be close to the gradients of the input image. The algorithm is data driven, stable, updates the surface slope and height maps simultaneously, and significantly reduces the residual errors in irradiance and integrability terms. A hierarchical implementation of the algorithm is presented. Typical results on synthetic and images are given to illustrate the usefulness of the approach     

A shape from shading analysis for a single perspective image of apolyhedron

A shape-from-shading analysis for a single perspective image of a polyhedron is presented. Given a single perspective image of a polyhedron, the depth of any point of the polyhedron from the camera, the direction of the light source illuminating the polyhedron and the albedo of the polyhedron, a system of algebraic equations are derived, which, when combined with edge information, quantitatively describes the shape of the polyhedron. This analysis is best possible in the sense that if any component of what the author has assumed is omitted, no similar analysis can provide the same results     

Shape from shading with a linear triangular element surface model

The authors propose to combine a triangular element surface model with a linearized reflectance map to formulate the shape-from-shading problem. The main idea is to approximate a smooth surface by the union of triangular surface patches called triangular elements and express the approximating surface as a linear combination of a set of nodal basis functions. Since the surface normal of a triangular element is uniquely determined by the heights of its three vertices (or nodes), image brightness can be directly related to nodal heights using the linearized reflectance map. The surface height can then be determined by minimizing a quadratic cost functional corresponding to the squares of brightness errors and solved effectively with the multigrid computational technique. The proposed method does not require any integrability constraint or artificial assumptions on boundary conditions. Simulation results for synthetic and real images are presented to illustrate the performance and efficiency of the method     

Digital step edges from zero crossing of second directional derivatives

We use the facet model to accomplish step edge detection. The essence of the facet model is that any analysis made on the basis of the pixel values in some neighborhood has its final authoritative interpretation relative to the underlying gray tone intensity surface of which the neighborhood pixel values are observed noisy samples. With regard to edge detection, we define an edge to occur in a pixel if and only if there is some point in the pixel's area having a negatively sloped zero crossing of the second directional derivative taken in the direction of a nonzero gradient at the pixel's center. Thus, to determine whether or not a pixel should be marked as a step edge pixel, its underlying gray tone intensity surface must be estimated on the basis of the pixels in its neighborhood. For this, we use a functional form consisting of a linear combination of the tensor products of discrete orthogonal polynomials of up to degree three. The appropriate directional derivatives are easily computed from this kind of a function. Upon comparing the performance of this zero crossing of second directional derivative operator with the Prewitt gradient operator and the Marr-Hildreth zero crossing of the Laplacian operator, we find that it is the best performer; next is the Prewitt gradient operator. The Marr-Hildreth zero crossing of the Laplacian operator performs the worst.     

Shape aware normal interpolation for curved surface shading from polyhedral approximation

Independent interpolation of local surface patches and local normal patches is an efficient way for fast rendering of smooth curved surfaces from rough polyhedral meshes. However, the independently interpolating normals may deviate greatly from the analytical normals of local interpolating surfaces, and the normal deviation may cause severe rendering defects when the surface is shaded using the interpolating normals. In this paper we propose two novel normal interpolation schemes along with interpolation of cubic Bézier triangles for rendering curved surfaces from rough triangular meshes. Firstly, the interpolating normal is computed by a Gregory normal patch to each Bézier triangle by a new definition of quadratic normal functions along cubic space curves. Secondly, the interpolating normal is obtained by blending side-vertex normal functions along side-vertex parametric curves of the interpolating Bézier surface. The normal patches by these two methods can not only interpolate given normals at vertices or boundaries of a triangle but also match the shape of the local interpolating surface very well. As a result, more realistic shading results are obtained by either of the two new normal interpolation schemes than by the traditional quadratic normal interpolation method for rendering rough triangular meshes.     

基于光学特性及其线性约束的图像检测算法

基于图像纹理和阴影的信息判断物理光学特性,根据该特性是否一致提出一种检测图像真实性的算法。通过建立线性规划方程限定楔形方向和角度,并运用共轭梯度法去判定正确的纹理信息。纹理限定的光源位置或楔形的交集都可以作为判定图像真实性的依据。结合阴影和纹理的约束条件,使得楔形的参数更加精确。实验结果显示,所建立的算法可以正确显示光源的信息和图像中物体的光学特性,并判断图像是否被篡改。     

On-the-fly texture computation for real-time surface shading

Standard texture mapping hardware enables rapid rendering of color mapped surfaces with interpolated surface shading. New algorithms extend this to bump mapping, Phong shading, and reflection mapping. We first introduce the bidirectional reflectance function we wish to optimize, split into diffuse, specular and environment terms. Casting the diffuse term as a table lookup, we introduce lighting tables and efficient ways to compute them for distant lights. We also revisit the geometry of bump mapping, extending Blinn's (1978) results. We consider caching intermediate results for rendering animated rigid bodies, generalizing this to animated surfaces using a technique called parametric rasterization. Finally, we describe efficient reflection mapping and discuss implications for bump-mapped surfaces. We present a fast method for rendering Phong highlights and discuss a special case of a planar surface with simulated water ripples     

一种基于轮廓提取与纹理分析的图像着色方法*

从分析卡通、漫画图像的构图方法入手提出一种基于颜色扩展的图像着色方法,通过提取图像轮廓边界形成着色方向场指导上色过程,利用Gabor小波实现对图像中非相邻纹理区域的分析与匹配.实验结果说明该方法通过简洁的色彩关系和明暗层次突出了卡通、漫画图像适度简化和夸张的艺术特点,不相邻区域纹理匹配有效简化了细节部分添加色彩标记的用户交互复杂度.     

Fingerprint classification by directional image partitioning

In this work, we introduce a new approach to automatic fingerprint classification. The directional image is partitioned into “homogeneous” connected regions according to the fingerprint topology, thus giving a synthetic representation which can be exploited as a basis for the classification. A set of dynamic masks, together with an optimization criterion, are used to guide the partitioning. The adaptation of the masks produces a numerical vector representing each fingerprint as a multidimensional point, which can be conceived as a continuous classification. Different search strategies are discussed to efficiently retrieve fingerprints both with continuous and exclusive classification. Experimental results have been given for the most commonly used fingerprint databases and the new method has been compared with other approaches known in the literature: As to fingerprint retrieval based on continuous classification, our method gives the best performance and exhibits a very high robustness     

基于医学图像的复杂曲面重建

为了更准确地重建复杂的三维医学数据模型,把二维医学图像轮廓线上的像素点转化为三维点云,引入经典的泊松点云重建技术。由于泊松重建的效果依赖于点云法向的准确性,针对轮廓线数据的特点,结合图像二维梯度方向,给出了点云法向的一致定向及基于已知定向进一步精确估计法向的方法。泊松重建方法作为一种隐式重建技术,可以很好地处理医学图像数据中经常存在的噪声、拓扑复杂等问题。鼻咽喉模型重建的结果说明,一致定向方法改进了传统的一致定向方法,得到了更为准确的医学重建模型。     

Estimation of sea surface currents based on ocean colour remote-sensing image analysis

Accurate quantification of the sea surface current speeds with high spatial resolution and in near real-time is beneficial for many applications of physical oceanography, and can be implemented by processing ocean colour remote-sensing imagery data. The robust optical flow (ROF) approach applied to sub-image processing is described in detail in this article, and compared with a conventional maximum cross-correlation (MCC) block matching algorithm with sub-pixel operation. ROF results obtained from Geostationary Ocean Colour Imager (GOCI) imagery are shown to be in good agreement with sea surface currents derived from Ocean Surface Current Analyses-Real time (OSCAR) data, providing a validation of the ROF method.     

Linear shape from shading

In many situations the reflectance function of a surface is approximately linear, and there is an effielent closed-form solution to the shape-from-shading problem. When boundary conditions (e.g., edges, singular points) are not available, good estimates of shape may still be extracted by using the assumption of general viewing position. An improved method for estimating the illuminant direction is also presented.     

物体表面明暗处理算法的研究

基于现在普遍应用的Phone光照模型而对曲面体表面离散成小多边形后进行明暗处理的方法进行了简单的陈述和比较,提出了改进的Phone明暗处理方法,采用Visual C＋＋实现程序,对Phone光照模型中的漫反射项中的L·N和镜面反射项中的N·H直接进行双线性插值,既保证了着色效果,又使Phone明暗处理的效率提高了近1/3。     

Spatial context-dependent multi-scale and directional image texture

This study evaluated image texture within a multi-scale context. The multi-scale texture profile is a representation of texture as a function of scale. It is related to the variogram, but has the advantage of being a direct measure of local texture over a specified kernel. Directional texture is a method to capture the dependence of texture on orientation using 1-dimensional kernels, and is potentially useful for quantifying texture for classes with a linear shape, such as roads or rivers. Seven derived texture attributes were proposed from the multi-scale texture profile and directional texture: the minimum, median, mean, maximum, range, minimum directional, and minimum multi-scale and directional texture. The derived texture attributes were found to be useful in developing a locally adaptive texture measure, which uses different texture attributes for different locations in the image. In order to develop the rules for the adaptive method, seven characteristic multi-scale texture profiles were identified. Rules were established to identify the general classes, and each pixel was assigned to one class only, depending on that pixel's texture profile. Optimal texture measures were proposed for each class. In an analysis using selected texture classes from IKONOS test data from Jeju, Korea, it was found that compared to all other texture measures, the adaptive texture provided the highest average and minimum classification accuracy, as well as the second highest maximum accuracy (69%, 51% and 92%, respectively). In comparison, the best fixed size kernel, 11?×?11 pixels, had accuracies in the same categories of 68%, 38% and 87%, and the original panchromatic image band had accuracies of 41%, 5% and 92%. Future work is needed to enhance the texture rules, and apply the adaptive texture method to other scales of data.     

An error analysis for surface orientation from vanishing points

Given two parallel lines in a plane, their images formed by central projection onto the viewing plane intersect at a vanishing point, which provides a constraint on the orientation of the plane. Two such independent constraints define a vanishing line and thereby determine the orientation of the plane uniquely. In order to effectively use this information, an estimate of its accuracy must be incorporated. In the approach suggested, line directions and surface normal vectors are represented as points on a Gaussian sphere, and the error bounds are computed as regions on the sphere. Information from multiple vanishing points and surfaces is combined by intersecting the corresponding regions. In addition, constraints based on real-world knowledge can be introduced to improve the accuracy. Some experimental results on natural images re presented to illustrate this method     

A class of adaptive directional image smoothing filters

The gray level distribution around a pixel of an image usually tends to be more coherent in some directions compared to other directions. The idea of adaptive directional filtering is to estimate the direction of higher coherence around each pixel location and then to employ a window which approximates a line segment in that direction. Hence, the details of the image may be preserved while maintaining a satisfactory level of noise suppression performance. In this paper we describe a class of adaptive directional image smoothing filters based on generalized Gaussian distributions. We propose a measure of spread for the pixel values based on the maximum likelihood estimate of a scale parameter involved in the generalized Gaussian distribution. Several experimental results indicate a significant improvement compared to some standard filters.     

Height and gradient from shading

The method described here for recovering the shape of a surface from a shaded image can deal with complex, wrinkled surfaces. Integrability can be enforced easily because both surface height and gradient are represented. (A gradient field is integrable if it is the gradient of some surface height function.) The robustness of the method stems in part from linearization of the reflectance map about the current estimate of the surface orientation at each picture cell. (The reflectance map gives the dependence of scene radiance on surface orientation.) The new scheme can find an exact solution of a given shape-from-shading problem even though a regularizing term is included. The reason is that the penalty term is needed only to stabilize the iterative scheme when it is far from the correct solution; it can be turned off as the solution is approached. This is a reflection of the fact that shape-from-shading problems are not ill posed when boundary conditions are available, or when the image contains singular points.This article includes a review of previous work on shape from shading and photoclinometry. Novel features of the new scheme are introduced one at a time to make it easier to see what each contributes. Included is a discussion of implementation details that are important if exact algebraic solutions of synthetic shape-from-shading problems are to be obtained. The hope is that better performance on synthetic data will lead to better performance on real data.Massachusetts Institute of Technology     

Local shape approximation from shading

Shading can be used as an independent cue for exact shape recovery, or it can be used as a supplementary cue for shape interpolation between features whose depths are known from other cues. Exact shape cannot be inferred from a local analysis of shading. However, for shape interpolation a crude local approximation may be sufficient. This paper explores the limits of such local approximations that are easy to compute. In particular, the shape of shading is used to approximate the surface in areas of monotonic change of intensity. This analysis is accompanied by a method for computing the direction of a single-point light source from the shading on occluding contours. A qualitative classification of shape near shading singularities is also discussed.This work was performed at the Massachusetts Institute of Technology, Center for Biological Information Processing.