Computational Cameras: Convergence of Optics and Processing
Computational Cameras: Convergence of Optics and Processing
复制标题
DOI：
10.1109/tip.2011.2171700
复制
发表时间：
2011-12-01
影响因子：
10.6
通讯作者：
Nayar, Shree K.
中科院分区：
文献类型：
--
作者：
Zhou, Changyin;Nayar, Shree K.
计算相机使用光学和处理的组合来产生传统相机无法捕捉到的图像。在过去的十年里，计算成像已经成为一个充满活力的研究领域。与传统相机相比，各种各样的计算相机已经被证明可以在捕获的图像中编码更有用的视觉信息。在本文中，我们从两个角度对计算相机进行了综述。首先，我们根据编码方法给出了计算摄像机设计的分类，包括物体侧编码、光瞳平面编码、传感器侧编码、照明编码、摄像机阵列和集群以及非传统成像系统。其次，我们使用光场表示的抽象概念作为描述计算相机设计的通用工具，其中每个相机可以被表示为高维光场到二维图像传感器的投影。我们展示了单个光学设备如何转换光场，并使用这些转换来说明不同的计算相机设计(光学设备集合)如何捕获和编码有用的视觉信息。
A computational camera uses a combination of optics and processing to produce images that cannot be captured with traditional cameras. In the last decade, computational imaging has emerged as a vibrant field of research. A wide variety of computational cameras has been demonstrated to encode more useful visual information in the captured images, as compared with conventional cameras. In this paper, we survey computational cameras from two perspectives. First, we present a taxonomy of computational camera designs according to the coding approaches, including object side coding, pupil plane coding, sensor side coding, illumination coding, camera arrays and clusters, and unconventional imaging systems. Second, we use the abstract notion of light field representation as a general tool to describe computational camera designs, where each camera can be formulated as a projection of a high-dimensional light field to a 2-D image sensor. We show how individual optical devices transform light fields and use these transforms to illustrate how different computational camera designs (collections of optical devices) capture and encode useful visual information.