All-in-focus with directional-max-gradient flow and labeled iterative depth propagation
作者：
Highlights：
• Highlights
• We propose directional-max-gradient flow to describe gradient propagation process.
• We design operators to classify source points into off-plane and in-plane edges.
• We propose labeled iterative depth propagation to get better all-in-focus image.
• Experiments show effectiveness of proposed algorithm on synthesized and real data.
摘要
Highlights•We propose directional-max-gradient flow to describe gradient propagation process.•We design operators to classify source points into off-plane and in-plane edges.•We propose labeled iterative depth propagation to get better all-in-focus image.•Experiments show effectiveness of proposed algorithm on synthesized and real data.
论文关键词：Focus stacking,Directional-max-gradient flow,Blur kernel,Depthmap,Laplacian optimization
论文评审过程：Received 23 December 2016, Revised 5 August 2017, Accepted 30 October 2017, Available online 31 October 2017, Version of Record 30 December 2017.
论文官网地址：https://doi.org/10.1016/j.patcog.2017.10.040
