Efficient auto-refocusing for light field camera
作者：
Highlights：
• Introducing an efficient ARF framework based on accurate estimation of R-PSF.
• Modelling the R-PSF via a detailed analysis of the relationship between refocusing depth and defocus blurriness.
• Constructing an absolute blurriness measure.
• Implementing an efficient ARF algorithm and evaluating the algorithm on four datasets.
• Applying the proposed ARF algorithm to iris recognition and quantizing its effectiveness and robustness via recognition scores.
摘要
•Introducing an efficient ARF framework based on accurate estimation of R-PSF.•Modelling the R-PSF via a detailed analysis of the relationship between refocusing depth and defocus blurriness.•Constructing an absolute blurriness measure.•Implementing an efficient ARF algorithm and evaluating the algorithm on four datasets.•Applying the proposed ARF algorithm to iris recognition and quantizing its effectiveness and robustness via recognition scores.
论文关键词：Auto-refocusing,Detection-based focusing,Blurriness measure,Light-field photography
论文评审过程：Received 31 January 2017, Revised 9 February 2018, Accepted 23 March 2018, Available online 30 March 2018, Version of Record 9 April 2018.
论文官网地址：https://doi.org/10.1016/j.patcog.2018.03.020
