Image segmentation algorithms often depend on appearance models that characterize the distribution of pixel values in different image regions. We describe a novel approach for estimating appearance models directly from an image, without explicit consideration of the pixels that make up each region. Our approach is based on algebraic expressions that relate local image statistics to the appearance models of spatially coherent regions. We describe two algorithms that can use the aforementioned algebraic expressions for estimating appearance models. The first algorithm is based on solving a system of linear and quadratic equations. The second algorithm is a spectral method based on an eigenvector computation. We present experimental results that demonstrate the proposed methods work well in practice and lead to effective image segmentation algorithms.

翻译：图像分离算法往往取决于不同图像区域像素值分布特征的外观模型。 我们描述一种直接从图像中估算外观模型的新颖方法,而没有明确考虑构成每个区域的像素。 我们的方法基于代数表达法,将本地图像统计与空间一致性区域的外观模型联系起来。 我们描述两种可使用上述代数表达法估计外观模型的算法。 第一种算法基于解决线性和二次方程的系统。 第二种算法是一种光谱方法,它基于源子计算法。 我们提出实验结果,表明拟议方法在实践中运作良好,并导致有效的图像分割算法。