Artificial Intelligence Center, SRI International, Menlo Park, CA 94025; Departments of Computer Science and Psychology, Stanford University, Stanford, CA 94305.
IEEE Trans Pattern Anal Mach Intell. 1984 Feb;6(2):170-87. doi: 10.1109/tpami.1984.4767501.
Local analysis of image shading, in the absence of prior knowledge about the viewed scene, may be used to provide information about the scene. The following has been proved. Every image point has the same image intensity and first and second derivatives as the image of some point on a Lambertian surface with principal curvatures of equal magnitude. Further, if the principal curvatures are assumed to be equal there is a unique combination of image formation parameters (up to a mirror reversal) that will produce a particular set of image intensity and first and second derivatives. A solution for the unique combination of surface orientation, etc., is presented. This solution has been extended to natural imagery by using general position and regional constraints to obtain estimates of the following: ¿ surface orientation at each image point; ¿ the qualitative type of the surface, i.e., whether the surface is planar, cylindrical, convex, concave, or saddle; ¿ the illuminant direction within a region. Algorithms to recover illuminant direction and estimate surface orientation have been evaluated on both natural and synthesized images, and have been found to produce useful information about the scene.
局部图像阴影分析，在缺乏对所观察场景的先验知识的情况下，可以用来提供有关场景的信息。以下已经得到证明。每个图像点的图像强度以及一阶和二阶导数都与具有相等大小主曲率的朗伯面的某个点的图像相同。此外，如果假设主曲率相等，则存在唯一的图像形成参数组合（最多进行镜像反转），将产生特定的一组图像强度以及一阶和二阶导数。提出了一种用于确定表面方向等的唯一组合的解决方案。通过使用一般位置和区域约束，将该解决方案扩展到自然图像中，以获得以下内容的估计：在每个图像点的表面方向；表面的定性类型，即表面是平面，圆柱，凸，凹还是鞍形；区域内的照明方向。已经在自然和合成图像上评估了恢复照明方向和估计表面方向的算法，并且发现它们可以提供有关场景的有用信息。
