We propose a novel piecewise smooth image model with piecewise constant local parameters that are automatically adapted to each image. Technically, the model is formulated in terms of factor graphs with NUP (normal with unknown parameters) priors, and the pertinent computations amount to iterations of conjugate-gradient steps and Gaussian message passing. The proposed model and algorithms are demonstrated with applications to denoising and contrast enhancement.

翻译：我们提出了一种新颖的分段平滑图像模型，其分段常数局部参数可自动适应每幅图像。从技术上讲，该模型通过具有NUP（参数未知的正态分布）先验的因子图进行表述，相关计算归结为共轭梯度迭代与高斯消息传递。所提出的模型与算法在去噪和对比度增强应用中得到了验证。