首页> 外文期刊>Image Processing, IEEE Transactions on >Nonlinear Approach for Enhancement of Image Focus Volume in Shape From Focus
【24h】

Nonlinear Approach for Enhancement of Image Focus Volume in Shape From Focus

机译:从焦点增强形状的图像焦点体积的非线性方法

获取原文
获取原文并翻译 | 示例
       

摘要

Mostly, shape-from-focus algorithms use local averaging using a fixed rectangle window to enhance the initial focus volume. In this linear filtering, the window size affects the accuracy of the depth map. A small window is unable to suppress the noise properly, whereas a large window oversmoothes the object shape. Moreover, the use of any window size smoothes focus values uniformly. Consequently, an erroneous depth map is obtained. In this paper, we suggest the use of iterative 3-D anisotropic nonlinear diffusion filtering (ANDF) to enhance the image focus volume. In contrast to linear filtering, ANDF utilizes the local structure of the focus values to suppress the noise while preserving edges. The proposed scheme is tested using image sequences of synthetic and real objects, and results have demonstrated its effectiveness.
机译:通常,聚焦形状算法使用固定矩形窗口的局部平均来增强初始聚焦量。在此线性滤波中,窗口大小会影响深度图的准确性。小窗口无法适当地抑制噪声,而大窗口会使物体的形状变得平滑。此外,任何窗口大小的使用都可以均匀地平滑焦点值。因此,获得了错误的深度图。在本文中,我们建议使用迭代3-D各向异性非线性扩散滤波(ANDF)来增强图像聚焦量。与线性滤波相反,ANDF利用焦点值的局部结构来抑制噪声,同时保留边缘。该方案通过合成和真实物体的图像序列进行了测试,结果证明了其有效性。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号