论文标题
泊松图像通过插件量子降级方案进行反卷积
Poisson Image Deconvolution by a Plug-and-Play Quantum Denoising Scheme
论文作者
论文摘要
本文使用Schroedinger方程的量子物理解决方案介绍了乘数（ADMM）方案的新的插件（PNP）交替方向（ADMM）方案。评估所提出的算法的效率用于泊松图像反卷积，这对于成像应用非常常见，例如有限的光子获取。数值结果表明，对于低和高信噪比的情况，与最近的最新技术相比，该方案的优势与最新的最新技术相比。这种性能增长主要是通过嵌入式量子DeNoiser在影响观测值的不同类型的噪声方面的灵活性来解释的。
This paper introduces a new Plug-and-Play (PnP) alternating direction of multipliers (ADMM) scheme based on a recently proposed denoiser using the Schroedinger equation's solutions of quantum physics. The efficiency of the proposed algorithm is evaluated for Poisson image deconvolution, which is very common for imaging applications, such as, for example, limited photon acquisition. Numerical results show the superiority of the proposed scheme compared to recent state-of-the-art techniques, for both low and high signal-to-noise-ratio scenarios. This performance gain is mostly explained by the flexibility of the embedded quantum denoiser for different types of noise affecting the observations.
