Representation and Recovery of Discontiniuties in Some Image Processing Problems

本文研究了稀疏深度数据的图像恢复、边缘检测和表面插值等图像处理问题中不连续点的恢复问题。提出了利用基本德曼过程和德曼线过程的自然泛化来处理任意实值方向和幅度，并利用贝塞格伪似然方法等方法来估计参数。

This proposal deals with the general problem of recovery of discontinuities in image processing problems such as image restoration, edge detection, and surface interpolation from sparse depth data. It proposes to use a natural generalization of the basic Geman and Geman line process to handle arbitrary real-valued directions and magnitudes, and methods such Besag's pseudo-likelihood methods to estimate parameters.