论文标题
通过非规范采样和关节稀疏反卷积和外推通过增加成像的分辨率
Increasing Imaging Resolution by Non-Regular Sampling and Joint Sparse Deconvolution and Extrapolation
论文作者
论文摘要
自多年来，增加图像传感器的分辨率一直是一场永无止境的斗争。在本文中，我们提出了一种新型的图像传感器布局，该布局允许以更高的分辨率和提高质量获取图像。为此，图像传感器利用非规范采样来减少混叠的影响。因此，它允许使用相同数量的像素的最新传感器捕获细节。通过以非规则方式旋转原型像素细胞来实现非规范的采样。由于不是像素电池的整个区域对光敏感，因此获得了入射光的非规范空间整合。基于传感器输出数据，可以通过对集成区域进行反卷积以及将信息推送到像素的不敏感区域来重建高分辨率图像。为了解决这项具有挑战性的任务，我们引入了一种新型的关节稀疏反卷积和外推算法。非规范采样和提出的重建的结合允许实现更高的分辨率，并具有改进的成像质量。
Increasing the resolution of image sensors has been a never ending struggle since many years. In this paper, we propose a novel image sensor layout which allows for the acquisition of images at a higher resolution and improved quality. For this, the image sensor makes use of non-regular sampling which reduces the impact of aliasing. Therewith, it allows for capturing details which would not be possible with state-of-the-art sensors of the same number of pixels. The non-regular sampling is achieved by rotating prototype pixel cells in a non-regular fashion. As not the whole area of the pixel cell is sensitive to light, a non-regular spatial integration of the incident light is obtained. Based on the sensor output data, a high-resolution image can be reconstructed by performing a deconvolution with respect to the integration area and an extrapolation of the information to the insensitive regions of the pixels. To solve this challenging task, we introduce a novel joint sparse deconvolution and extrapolation algorithm. The union of non-regular sampling and the proposed reconstruction allows for achieving a higher resolution and therewith an improved imaging quality.
