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首页> 外文会议>3DTV Conference: The True Vision - Capture, Transmission and Display of 3D Video, 2009 >Simultaneous estimation of super-resolved depth and all-in-focus images from a plenoptic camera
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Simultaneous estimation of super-resolved depth and all-in-focus images from a plenoptic camera

机译：同时估计全光摄像机的超分辨深度和全焦点图像

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This paper presents a new technique to simultaneously estimate the depth map and the all-in-focus image of a scene, both at super-resolution, from a plenoptic camera. A plenoptic camera uses a microlens array to measure the radiance and direction of all the light rays in a scene. It is composed of nxn microlenses and each of them generates a mxm image. Previous approaches to the depth and all-in- focus estimation problem processed the plenoptic image, generated a nxnxm focal stack, and were able to obtain a nxn depth map and all-in-focus image of the scene. This is a major drawback of the plenoptic camera approach to 3DTV since the total resolution of the camera n2m2 is divided by m2 to obtain a final resolution of n2 pixels. In our approach we propose a new super-resolution focal stack that is combined with multiview depth estimation. This technique allows a theoretical resolution of approximately n2m2/4 pixels. This is an o(m2) increment over previous approaches. From a practical point of view, in typical scenes we are able to increase 25 times the resolution of previous techniques. The time complexity of the algorithm makes possible to obtain real-time processing for 3DTV using appropriate hardware (GPU's or FPGA's) so it could be used in plenoptic video-cameras.
机译：本文提出了一种新技术，可以同时从全光摄像机以超分辨率同时估算景深图和全焦点图像。全光相机使用微透镜阵列来测量场景中所有光线的辐射度和方向。它由nxn个微透镜组成，每个微透镜都生成一个mxm图像。以前针对深度和全焦点估计问题的方法处理了全光图像，生成了nxnxm焦距堆栈，并且能够获得场景的nxn深度图和全焦点图像。这是全光摄像机用于3DTV的主要缺点，因为摄像机的总分辨率n 2 m 2 除以m 2 即可获得n 2 像素的最终分辨率。在我们的方法中，我们提出了一种新的超分辨率焦距堆栈，该堆栈与多视图深度估计结合在一起。此技术的理论分辨率约为n 2 m 2 / 4个像素。与以前的方法相比，这是o（m 2 ）的增量。从实际的角度来看，在典型场景中，我们能够将分辨率提高到以前技术的25倍。该算法的时间复杂性使得可以使用适当的硬件（GPU或FPGA）获得3DTV的实时处理，因此可以在全光摄像机中使用。

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