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Measure of image focus using image segmentation and SML for light field images

Authors: Wisarut Chantara; Yo-Sung Ho;

Measure of image focus using image segmentation and SML for light field images

Abstract

In this paper, a detection method of in-focused regions in the light field stack images is proposed. Its main motivation is that the focus measure with region-based image algorithms can be more meaningful than the focus measure with pixel-based algorithms which just consider individual pixels or associated local neighborhoods of pixels in the focus measure process. After we employ the normalized cut method to segment the light field stack images, we apply the sum-modified-Laplacian operation to the corresponding segmented regions. This process provides a focus measurement to select suitable in-focused areas of the stack images. Since only sharply focused regions have high responses, the in-focused regions can be detected. In addition, the all-focused image can be reconstructed by combining all in-focused image regions.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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Average
Average
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