2015
DOI: 10.1007/s10732-015-9291-4
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An autofocus heuristic for digital cameras based on supervised machine learning

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Cited by 16 publications
(10 citation statements)
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“…Specifically, by integrating phase detection AF and contrast AF, as described above, to compensate for the respective AF methods' shortcomings, the speed and accuracy of AF in CSC were improved. The phase detection AF method's drawback is that the actual focal position does not match due to AF computation movement [10]. Therefore, if it is supplemented with contrast AF, that focuses accurately, it is possible to focus on fast-moving objects even in dark surroundings.…”
Section: Introductionmentioning
confidence: 99%
“…Specifically, by integrating phase detection AF and contrast AF, as described above, to compensate for the respective AF methods' shortcomings, the speed and accuracy of AF in CSC were improved. The phase detection AF method's drawback is that the actual focal position does not match due to AF computation movement [10]. Therefore, if it is supplemented with contrast AF, that focuses accurately, it is possible to focus on fast-moving objects even in dark surroundings.…”
Section: Introductionmentioning
confidence: 99%
“…Mir et al . (), unlike above publications, considered the case of multimodal model and implemented a machine learning‐based coarse‐to‐fine search to find all the peaks, typically the foreground and background. This method does not fall with the scope of this study, which is the unimodality of the model; indeed, our specimens are such they can be imaged at one time by the SEM.…”
Section: Introductionmentioning
confidence: 99%
“…It is easier to implement than the method of Mir et al . (), since it is just a regression and only requires an off‐line automatic training to determine its parameters. Finally, the solution is an efficient autofocus method that works well at low and high magnifications.…”
Section: Introductionmentioning
confidence: 99%
“…Other types of strategies are motivated by reducing the time and stack size to find the image with the best focus (e.g., maximizing the number of ROIs in focus). These strategies are based on optimization methods to estimate some extreme point of a function (e.g., maximum of a focus function) [32,35,36,57]. • Stitching: This is the process carried out to obtain an image composed by several images with overlapping FOVs.…”
mentioning
confidence: 99%
“…• (1-DIG) Multifocus and multiexposure fusion: When several images are captured at different focal planes, the inherent three-dimensional morphology of diatom valves is recorded and could be fused in a new complete in focus image. Similarly, multiexposure fusion is used to obtain the right exposure over all regions in the fused image from individual images with underexposed and overexposed regions[9,10,13,[30][31][32][33][34][35][36].• …”
mentioning
confidence: 99%