Mahmood Muhammad Tariq
School of Computer Science and Engineering, Korea University of Technology and Education, Cheonan, 31253, Republic of Korea.
Microsc Res Tech. 2019 Jun;82(6):872-877. doi: 10.1002/jemt.23230. Epub 2019 Feb 18.
In shape from focus (SFF) methods, image focus volume enhancement is an important issue for acquiring accurate depth maps. Mostly, conventional approaches do focus aggregation locally to enhance the focus volume, which may not suppress noisy focus measurements properly and consequently, may provide deteriorated depth maps. Multiresolution fusion-based method is proposed for image focus volume enhancement. First, an initial focus volume is obtained by applying a conventional focus measure. Then, a pyramid of focus volumes is computed using Gaussian filters and subsampling. Focus measures from various focus volumes at different levels are merged into a single resultant focus volume. Finally, the depth map is obtained from the resultant focus volume by maximizing the focus measure in the optical-axis direction. According to the best of my knowledge, the cross-scale aggregation has never been used in enhancing the image focus volume in SFF. The proposed method is evaluated through the experiments using image sequences of real microscopic and simulated objects. Results comparisons based on root mean square error (RMSE) and correlation demonstrate the effectiveness of the proposed method in improving the focus volume and depth map. The proposed fusion method of volumes is a simple but effective. The idea of cross-scale aggregation of focus measures is effective in providing precise focus measures that consequently, provide accurate depth map. In future work, it will further be explored and a more sophisticated and optimization-based fusion algorithm will be applied.
在聚焦形状（SFF）方法中，图像聚焦体积增强是获取精确深度图的一个重要问题。大多数情况下，传统方法在局部进行聚焦聚合以增强聚焦体积，这可能无法恰当地抑制有噪声的聚焦测量，因此可能会提供质量下降的深度图。本文提出了一种基于多分辨率融合的方法来增强图像聚焦体积。首先，通过应用传统聚焦度量获得初始聚焦体积。然后，使用高斯滤波器和下采样计算聚焦体积的金字塔。来自不同级别各种聚焦体积的聚焦度量被合并成一个单一的最终聚焦体积。最后，通过在光轴方向上最大化聚焦度量从最终聚焦体积中获得深度图。据我所知，跨尺度聚合从未被用于增强SFF中的图像聚焦体积。通过使用真实微观和模拟物体的图像序列进行实验对所提出的方法进行了评估。基于均方根误差（RMSE）和相关性的结果比较证明了所提出的方法在改善聚焦体积和深度图方面的有效性。所提出的体积融合方法简单但有效。聚焦度量的跨尺度聚合思想在提供精确聚焦度量从而提供准确深度图方面是有效的。在未来的工作中，将进一步进行探索并应用更复杂的基于优化的融合算法。
