论文标题
通过基于相关匹配的一对非规范采样传感器拍摄的图像重建图像
Reconstruction of images taken by a pair of non-regular sampling sensors using correlation based matching
论文作者
论文摘要
由于需要的高分辨率图像传感器的数量，具有两个或多个相机的多视图图像采集系统可能会成本高昂。最近，已经表明，通过覆盖具有非规范采样蒙版的低分辨率传感器，并使用有效的算法进行图像重建，可以获得高分辨率图像。在本文中，提出了用于多视图方案的立体图像重建设置。一对非规范采样传感器捕获了场景，并通过从相邻视图中合并信息，可以提高重建质量。与最先进的单视重建算法相比，这导致PSNR的视觉平均增益为0.74 dB。
Multi-view image acquisition systems with two or more cameras can be rather costly due to the number of high resolution image sensors that are required. Recently, it has been shown that by covering a low resolution sensor with a non-regular sampling mask and by using an efficient algorithm for image reconstruction, a high resolution image can be obtained. In this paper, a stereo image reconstruction setup for multi-view scenarios is proposed. A scene is captured by a pair of non-regular sampling sensors and by incorporating information from the adjacent view, the reconstruction quality can be increased. Compared to a state-of-the-art single-view reconstruction algorithm, this leads to a visually noticeable average gain in PSNR of 0.74 dB.
