Recovering Shading from Color Images

نویسندگان

  • Brian V. Funt
  • Mark S. Drew
  • Michael Brockington
چکیده

Existing shape-from-shading algorithms assume constant reflectance across the shaded surface. Multi-colored surfaces are excluded because both shading and reflectance affect the measured image intensity. Given a standard RGB color image, we describe a method of eliminating the reflectance effects in order to calculate a shading field that depends only on the relative positions of the illuminant and surface. Of course, shading recovery is closely tied to lightness recovery and our method follows from the work of Land [10, 9], Horn [7] and Blake [1]. In the luminance image, R+G+B, shading and reflectance are confounded. Reflectance changes are located and removed from the luminance image by thresholding the gradient of its logarithm at locations of abrupt chromaticity change. Thresholding can lead to gradient fields which are not conservative (do not have zero curl everywhere and are not integrable) and therefore do not represent realizable shading fields. By applying a new curl-correction technique at the thresholded locations, the thresholding is improved and the gradient fields are forced to be conservative. The resulting Poisson equation is solved directly by the Fourier transform method. Experiments with real images are presented.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Color Constancy, Intrinsic Images, and Shape Estimation

We present SIRFS (shape, illumination, and reflectance from shading), the first unified model for recovering shape, chromatic illumination, and reflectance from a single image. Our model is an extension of our previous work [1], which addressed the achromatic version of this problem. Dealing with color requires a modified problem formulation, novel priors on reflectance and illumination, and a ...

متن کامل

A Divide-and-conquer Strategy in Recovering Surface Shape of Book from Shading

A divide-and-conquer strategy in shape from shading is proposed for recovering book surface on fully perspective condition. It is shown that unique shape can be recovered despite of more unknowns than shade images by dividing original implicit SFS problem into explicit ones. Using invariance of shading, a transformed shading equation and a recurrence relation is derived for depth recovery. Whol...

متن کامل

Beyond Lambertian Shape from Shading

Traditional shape from shading methods are based on the Lambertian surface model. Real images often contain specularities which violate this assumption and lead to undesired results. In [1] a method for color subspace based specularity removal has been proposed. This method only works with a good estimate of the source color given as a vector in RGB space. In this project we present two novel m...

متن کامل

The Color Constancy Problem: An Illumination Invariant Mapping Approach

We suggest a novel approach to the Color Constancy Problem for multispectral imagery. Our approach is based on a dichromatic illumination model and lters out all spectral information which possibly stems from the illumination rather than from the re ectance of a given surface. Instead of recovering the re ectance signal, the suggested mapping produces a new only surface re ectance-dependent des...

متن کامل

Shapes, Paint, and Light

Shapes, Paint, and Light by Jonathan Tilton Barron Doctor of Philosophy in Computer Science University of California, Berkeley Professor Jitendra Malik, Chair A fundamental problem in computer vision is that of inferring the intrinsic, 3D structure of the world from flat, 2D images of that world. Traditional methods for recovering scene properties such as shape, reflectance, or illumination rel...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 1992