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Harmonic Variance: A Novel Measure for In-focus Segmentation
Author(s) -
Feng Li,
Fatih Porikli
Publication year - 2013
Language(s) - English
Resource type - Conference proceedings
DOI - 10.5244/c.27.33
Subject(s) - measure (data warehouse) , focus (optics) , computer science , variance (accounting) , segmentation , harmonic measure , artificial intelligence , mathematics , data mining , optics , physics , harmonic function , accounting , mathematical analysis , economics
We introduce an efficient measure for estimating the degree of in-focus within an image region. This measure, harmonic mean of variances, is computed from the statistical properties of the image in its bandpass filtered versions. We incorporate the harmonic variance into a graph Laplacian spectrum based segmentation framework in order to accurately align the in-focus measure responses on the underlying image structure. Our results demonstrate the effectiveness of this novel measure for determining and segmenting in-focus regions in low depth-of-field images.

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