M
Murali Subbarao
Researcher at Stony Brook University
Publications - 54
Citations - 2666
Murali Subbarao is an academic researcher from Stony Brook University. The author has contributed to research in topics: Image restoration & Machine vision. The author has an hindex of 19, co-authored 54 publications receiving 2563 citations. Previous affiliations of Murali Subbarao include State University of New York System.
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Journal ArticleDOI
Depth from defocus: a spatial domain approach
Murali Subbarao,Gopal Surya +1 more
TL;DR: A new method named STM is described for determining distance of objects and rapid autofocusing of camera systems based on a new Spatial-Domain Convolution/Deconvolution Transform that requires only two images taken with different camera parameters such as lens position, focal length, and aperture diameter.
Journal ArticleDOI
Selecting the optimal focus measure for autofocusing and depth-from-focus
Murali Subbarao,J.-K. Tyan +1 more
TL;DR: A method is described for selecting the optimal focus measure with respect to gray-level noise from a given set of focus measures in passive autofocusing and depth-from-focus applications based on two new metrics that have been defined for estimating the noise-sensitivity of different focus measures.
Journal ArticleDOI
Accurate recovery of three-dimensional shape from image focus
Murali Subbarao,Tao Choi +1 more
TL;DR: The shape of the FIS is determined by searching for a shape which maximizes a focus measure, which results in more accurate shape recovery than the traditional methods.
Proceedings ArticleDOI
Parallel Depth Recovery By Changing Camera Parameters
TL;DR: In this paper, a new method is described for recovering the distance of objects in a scene from images formed by lenses, based on measuring the change in the scene's image due to a known change in three intrinsic camera parameters: (i) distance between the lens and the image detector, (ii) focal length, and (iii) diameter of the lens aperture.
Journal ArticleDOI
Focused image recovery from two defocused images recorded with different camera settings
TL;DR: In this article, two new methods are presented for recovering the focused image of an object from only two blurred images recorded with different camera parameters, including lens position, focal length, and aperture diameter.