Lee Joon-Jae, Lee Byung-Gook, Yoo Hoon
Department of Game Mobile Contents, Keimyung University, Daemyung3-Dong Nam-Gu, Daegu 705-701, South Korea.
Appl Opt. 2011 Oct 10;50(29):5624-9. doi: 10.1364/AO.50.005624.
We describe a computational method for depth extraction of three-dimensional (3D) objects using block matching for slice images in synthetic aperture integral imaging (SAII). SAII is capable of providing high-resolution 3D slice images for 3D objects because the picked-up elemental images are high-resolution ones. In the proposed method, the high-resolution elemental images are recorded by moving a camera; a computational reconstruction algorithm based on ray backprojection generates a set of 3D slice images from the recorded elemental images. To extract depth information of the 3D objects, we propose a new block-matching algorithm between a reference elemental image and a set of 3D slice images. The property of the slices images is that the focused areas are the right location for an object, whereas the blurred areas are considered to be empty space; thus, this can extract robust and accurate depth information of the 3D objects. To demonstrate our method, we carry out the preliminary experiments of 3D objects; the results indicate that our method is superior to a conventional method in terms of depth-map quality.
我们描述了一种计算方法，用于在合成孔径积分成像（SAII）中使用块匹配从切片图像提取三维（3D）物体的深度。SAII能够为3D物体提供高分辨率的3D切片图像，因为所采集的基元图像是高分辨率的。在所提出的方法中，通过移动相机记录高分辨率基元图像；基于光线反向投影的计算重建算法从记录的基元图像生成一组3D切片图像。为了提取3D物体的深度信息，我们提出了一种在参考基元图像和一组3D切片图像之间的新块匹配算法。切片图像的特性是聚焦区域是物体的正确位置，而模糊区域被认为是空的空间；因此，这可以提取3D物体的稳健且准确的深度信息。为了演示我们的方法，我们对3D物体进行了初步实验；结果表明，我们的方法在深度图质量方面优于传统方法。
