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Efficient auto-refocusing for light field camera
Chi Zhang; Guangqi Hou; Zhaoxiang Zhang; Zhenan Sun; Tieniu Tan
Source PublicationPattern Recognition
AbstractComputer 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 deter- mine 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.
KeywordAuto-refocusing Detection-based Focusing Blurriness Measure Light-field Photography
Document Type期刊论文
Recommended Citation
GB/T 7714
Chi Zhang,Guangqi Hou,Zhaoxiang Zhang,et al. Efficient auto-refocusing for light field camera[J]. Pattern Recognition,2018(81):176-189.
APA Chi Zhang,Guangqi Hou,Zhaoxiang Zhang,Zhenan Sun,&Tieniu Tan.(2018).Efficient auto-refocusing for light field camera.Pattern Recognition(81),176-189.
MLA Chi Zhang,et al."Efficient auto-refocusing for light field camera".Pattern Recognition .81(2018):176-189.
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