Shao Pei-Chiang
Department of Mathematics, Soochow University, Taipei City 111002, Taiwan.
Sensors (Basel). 2022 Mar 15;22(6):2271. doi: 10.3390/s22062271.
Reflections often cause degradation in image quality for pictures taken through glass medium. Removing the undesired reflections is becoming increasingly important. For human vision, it can produce much more pleasing results for multimedia applications. For machine vision, it can benefit various applications such as image segmentation and classification. Reflection removal is itself a highly illposed inverse problem that is very difficult to solve, especially for a single input image. Existing methods mainly rely on various prior information and assumptions to alleviate the ill-posedness. In this paper, we design a variational model based on multiscale hard thresholding to both effectively and efficiently suppress image reflections. A direct solver using the discrete cosine transform for implementing the proposed variational model is also provided. Both synthetic and real glass images are used in the numerical experiments to compare the performance of the proposed algorithm with other representative algorithms. The experimental results show the superiority of our algorithm over the previous ones.
对于通过玻璃介质拍摄的图片，反射常常会导致图像质量下降。去除不必要的反射变得越来越重要。对于人类视觉而言，这能为多媒体应用产生更令人满意的结果。对于机器视觉，它能使诸如图像分割和分类等各种应用受益。反射去除本身是一个高度不适定的逆问题，很难解决，尤其是对于单个输入图像。现有方法主要依靠各种先验信息和假设来缓解不适定性。在本文中，我们设计了一种基于多尺度硬阈值处理的变分模型，以有效且高效地抑制图像反射。还提供了一种使用离散余弦变换来实现所提出变分模型的直接求解器。数值实验中使用了合成玻璃图像和真实玻璃图像，以将所提出算法的性能与其他代表性算法进行比较。实验结果表明我们的算法优于先前的算法。
