基于梯度的立体图像快速网格生成方法

Ilkwon Park, H. Byun
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引用次数: 0

摘要

提出了一种基于梯度的快速立体图像网格生成方法。在我们的方法中,立体图像和中间视图中的右图像基本上是通过使用规则网格的二维图像翘曲从左图像预测和合成的,反之亦然。为了克服物体边界上的纹理失真,保持均匀区域的纹理平滑,我们提出在梯度图的强边缘上进行节点选择。通过立体匹配误差对所选节点进行评估,并对节点视差进行交叉验证。每个节点点都沿着梯度值高的像素迭代移动,而不是每个点都找到最优节点位置。因此,我们的方法提供了快速的网格优化以及可靠的图像质量。实验结果表明,与现有方法相比,该方法具有较高的计算效率和预测图像的高PSNR。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fast gradient-based mesh generation method for the stereo image representation
This paper proposes a fast gradient-based mesh generation method for the stereo image representation. In our approach, right image in stereo image and intermediate views are fundamentally predicted and synthesized from left image by 2D image warping using regular mesh and vice versa. To overcome texture distortion on object boundaries and preserve texture smoothness of homogenous areas, we propose node selection on the strong edges in the gradient map. Furthermore, the selected nodes are evaluated by stereo matching error and validated by cross validation for nodal disparity. Each node point is iteratively moving along the pixels with high gradient value instead every point to find the optimal node position. Therefore, our approach provides a fast mesh optimization as well as a reliable image quality. The experimental results show that the proposed approach provides computational efficiency and high PSNR of prediction image compared to previous methods.
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