Lam Edmund Y
J Opt Soc Am A Opt Image Sci Vis. 2015 Nov 1;32(11):2021-32. doi: 10.1364/JOSAA.32.002021.
Photography is a cornerstone of imaging. Ever since cameras became consumer products more than a century ago, we have witnessed great technological progress in optics and recording mediums, with digital sensors replacing photographic films in most instances. The latest revolution is computational photography, which seeks to make image reconstruction computation an integral part of the image formation process; in this way, there can be new capabilities or better performance in the overall imaging system. A leading effort in this area is called the plenoptic camera, which aims at capturing the light field of an object; proper reconstruction algorithms can then adjust the focus after the image capture. In this tutorial paper, we first illustrate the concept of plenoptic function and light field from the perspective of geometric optics. This is followed by a discussion on early attempts and recent advances in the construction of the plenoptic camera. We will then describe the imaging model and computational algorithms that can reconstruct images at different focus points, using mathematical tools from ray optics and Fourier optics. Last, but not least, we will consider the trade-off in spatial resolution and highlight some research work to increase the spatial resolution of the resulting images.
摄影是成像的基石。自一个多世纪前相机成为消费品以来，我们见证了光学和记录介质方面的巨大技术进步，在大多数情况下，数字传感器已取代了摄影胶片。最新的革命是计算摄影，它试图使图像重建计算成为图像形成过程中不可或缺的一部分；通过这种方式，整个成像系统可以具备新的功能或更好的性能。该领域的一项主要成果是全光相机，其旨在捕捉物体的光场；然后，合适的重建算法可以在图像拍摄后调整焦距。在这篇教程论文中，我们首先从几何光学的角度阐述全光函数和光场的概念。接下来讨论全光相机构造方面的早期尝试和最新进展。然后，我们将使用光线光学和傅里叶光学的数学工具，描述能够在不同焦点处重建图像的成像模型和计算算法。最后但同样重要的是，我们将考虑空间分辨率方面的权衡，并重点介绍一些提高所得图像空间分辨率的研究工作。
