【摘要】 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。更多还原

【Abstract】 We present an algorithm for color image understanding, which segments the image after analyzing surface with color variations due to lighting condition and object colors. The work is based on a theory—the Dichromatic Reflection Model—whilch describes the color of the reflected light as a linear combination of light from surface reflection (highlight) and body reflection (object color). A peculiar cluster shape (skewed T) is formed by color pixels of an object area in 3D histogram in color space. The analysis of cluster property helps to determine the color of light and objects, but at the same time, the meaningful cluster is generated by the projection of certain object area of the image. According to the strategy of hypothesis and test, following the continuity of the image and the feature of color clusters, the algorithm completes image segmentation and gives forth the physical description of imaging process, including intrinsic images, segmented image, the color of light and objects. Reflecting respectively the properties of light condition and every object, both the matte image and highlight image compose the intriusic images.更多还原