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2D-To-3D Stereoscopic Conversion: Depth-Map Estimation in a 2D Single-View Image

机译:2D-3D立体转换:2D单视图图像中的深度映射估计

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With increasing demands of 3D contents, conversion of many existing two-dimensional contents to three-dimensional contents has gained wide interest in 3D image processing. It is important to estimate the relative depth map in a single-view image for the 2D-To-3D conversion technique In this paper, we propose an automatic conversion method that estimates the depth information of a single-view image based on degree of focus of segmented regions and then generates a stereoscopic image. Firstly, we conduct image segmentation to partition an image into homogeneous regions. Then, we construct a higher-order statistics (HOS) map, which represents the spatial distribution of high-frequency components of the input image the HOS is known to be well suited for solving detection and classification problems because it can suppress Gaussian noise and preserve some of non-Gaussian information We can estimate a relative depth map with these two cues and then refine the depth map by post-processing Finally, a stereoscopic image is generated by calculating the parallax values of each region using the generated depth-map and the input image.
机译:随着3D内容的需求的增加,许多现有的二维内容的转换为三维内容已经获得了对3D图像处理的兴趣。重要的是在本文中估计用于2D-3D转换技术的单视图中的相对深度图,我们提出了一种自动转换方法,其基于焦点估计单视图图像的深度信息分段区域,然后产生立体图像。首先,我们进行图像分割以将图像分配到同质区域中。然后,我们构建一个高阶统计(HOS)映射,它表示输入图像的高频分量的空间分布,所知的HOS非常适合于解决检测和分类问题,因为它可以抑制高斯噪声和保留一些非高斯信息我们可以估计具有这两个线索的相对深度图,然后通过后处理来优化深度图,通过使用生成的深度映射计算每个区域的视差值来生成立体图像。输入图像。

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