Harmonic variance: A novel measure for in-focus segmentation

Abstract

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 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 infocus regions in low depth-of-field images.