3D shape from focus using LULU operators

Authors:
Roushanak Rahmat;Aamir Saeed Mallik;Nidla Kamel;Tae-Sun Choi;Monson H. Hayes
Affiliations:
Graduate School of Advanced Imaging Science, Multimedia, and Film, Chung-Ang University, Seoul, Korea;Center for Intelligent Signal & Imaging Research (CISIR) Department of Electrical and Electronic Engineering, Universiti Teknologi Petronas, Perak, Malaysia;Center for Intelligent Signal & Imaging Research (CISIR) Department of Electrical and Electronic Engineering, Universiti Teknologi Petronas, Perak, Malaysia;Department of Mechatronics, Gwangju Institute of Science and Technology, Gwangju, Korea;Graduate School of Advanced Imaging Science, Multimedia, and Film, Chung-Ang University, Seoul, Korea
Venue:
ACIVS'12 Proceedings of the 14th international conference on Advanced Concepts for Intelligent Vision Systems
Year:
2012

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Abstract

Extracting the shape of an object is one of the important tasks to be performed in many vision applications. One of the difficult challenges in 3D shape extraction is the roughness of the surfaces of objects. Shape from focus (SFF) is a shape recovery method that reconstructs the shape of an object from a sequence of images taken from the same viewpoint but with different focal lengths. This paper proposes the use of LULU operators as a preprocessing step to improve the signal-to-noise ratio in the estimation of 3D shape from focus. LULU operators are morphological filters that are used for their structure preserving properties. The proposed technique is tested on simulated and real images separately, as well as in combination with traditional SFF methods such as sum modified Laplacian (SML), and gray level variance (GLV). The proposed technique is tested in the presence of impulse noise with different noise levels. Based on the quantitative and qualitative experimental results it is shown that the proposed techniques is more accurate in focus value extraction and shape recovery in the presence of noise.