.png){kind=icon}
.png){kind=icon}
Return
Efficient auto-refocusing for light field camera
.png){kind=icon}
PRE
AI
DOI：10.1016/j.patcog.2018.03.020.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Computer vision tasks prefer the images focused at the related objects for a better performance, which requests a Auto-ReFocusing (ARF) function for using light field cameras. However, the current ARF schemes are time-consuming in practice, because they commonly need to render an image sequence for finding the optimally refocused frame. This paper presents an efficient ARF solution for light-field cameras based on modeling the refocusing point spread function (R-PSF). The R-PSF holds a simple linear relationship between refocusing depth and defocus blurriness. Such a linear relationship enables to determine the two candidates of the optimally refocused frame from only one initial refocused image. Because our method only involves three times of refocusing rendering for finding the optimally refocused frame, it is much more efficient than the current rendering and selection solutions which need to render a large number of refocused images. (C) 2018 Elsevier Ltd. All rights reserved.
Keywords:
Auto-refocusing
Detection-based focusing
Blurriness measure
Light-field photography
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.