论文标题
盲人问题的操作员和图像的平行扩散模型
Parallel Diffusion Models of Operator and Image for Blind Inverse Problems
论文作者
论文摘要
基于扩散模型的逆问题求解器在已知前向操作员（即非盲）的情况下证明了最先进的性能。但是，该方法在盲目的逆问题上的适用性尚未探讨。在这项工作中，我们表明，我们确实可以通过构建前向操作员的另一个扩散来解决一个盲人逆问题。具体而言，由中间阶段的梯度引导的并行反向扩散使前向操作员参数和图像的关节优化，因此两者在平行反向扩散过程结束时共同估计。我们显示了我们方法对两个代表性任务的功效 - 盲目的脱毛和通过湍流进行成像 - 并表明我们的方法会产生最新的性能，同时也可以灵活地适用于我们知道功能形式时适用于一般的盲目逆问题。
Diffusion model-based inverse problem solvers have demonstrated state-of-the-art performance in cases where the forward operator is known (i.e. non-blind). However, the applicability of the method to blind inverse problems has yet to be explored. In this work, we show that we can indeed solve a family of blind inverse problems by constructing another diffusion prior for the forward operator. Specifically, parallel reverse diffusion guided by gradients from the intermediate stages enables joint optimization of both the forward operator parameters as well as the image, such that both are jointly estimated at the end of the parallel reverse diffusion procedure. We show the efficacy of our method on two representative tasks -- blind deblurring, and imaging through turbulence -- and show that our method yields state-of-the-art performance, while also being flexible to be applicable to general blind inverse problems when we know the functional forms.
