Defocus map estimation from a single image

• Published in: Pattern recognition Vol. 44; no. 9; pp. 1852 - 1858
• Main Authors: Zhuo, Shaojie, Sim, Terence
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.09.2011
• Subjects: Ambiguity; Defocus blur; Defocus magnification; Defocus map; Estimates; Gaussian; Gaussian gradient; Image processing; Kernels; Pattern recognition; Propagation; Recovering; Gaussian gradient; Image processing; Defocus blur; Defocus magnification; Defocus map
• ISSN: 0031-3203; 1873-5142
• DOI: 10.1016/j.patcog.2011.03.009

In this paper, we address the challenging problem of recovering the defocus map from a single image. We present a simple yet effective approach to estimate the amount of spatially varying defocus blur at edge locations. The input defocused image is re-blurred using a Gaussian kernel and the defocus blur amount can be obtained from the ratio between the gradients of input and re-blurred images. By propagating the blur amount at edge locations to the entire image, a full defocus map can be obtained. Experimental results on synthetic and real images demonstrate the effectiveness of our method in providing a reliable estimation of the defocus map. ► We address the challenging problem of defocus estimation from a single image. ► The defocus blur is estimated at edge locations from the gradient ratio between tlie original and re-blurred input image. ► A hill defocus map is obtained by propagating the blur amount at edges to the entire image using soft matting. ► We also discuss the ambiguities in defocus estimation and the relationship between defocus map and depth.