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Noise Reduction using Mean Shift Algorithm for Estimating 3D Shape

Malik , Aamir Saeed and Shim, Seongo and Choi, Tae-Sun (2011) Noise Reduction using Mean Shift Algorithm for Estimating 3D Shape. [Citation Index Journal]

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Abstract

The technique to estimate the three-dimensional (3D) geometry of an object from a sequence of images obtained at different focus settings is called shape from focus (SFF). In SFF, the measure of focus – sharpness – is the crucial part for final 3D shape estimation. However, it is difficult to compute accurate and precise focus value because of the noise presence during the image acquisition by imaging system. Various noise filters can be employed to tackle this problem but they also remove the sharpness information in addition to the noise. In this paper, we propose a method based on mean shift algorithm to remove noise introduced by the imaging process while minimizing loss of edges. We test the algorithm in the presence of Gaussian noise and Impulse noise. Experimental results show that the proposed algorithm based on the mean shift algorithm provides better results than the traditional focus measures in the presence of the above mentioned two types of noise.

Item Type:Citation Index Journal
Impact Factor:2009 Impact factor: 0.169; 5-Year Impact factor: 0.287
Subjects:T Technology > TK Electrical engineering. Electronics Nuclear engineering
Departments / MOR / COE:Centre of Excellence > Center for Intelligent Signal and Imaging Research
Departments > Electrical & Electronic Engineering
Research Institutes > Institute for Health Analytics
ID Code:6613
Deposited By: Dr Aamir Saeed Malik
Deposited On:27 Oct 2011 00:31
Last Modified:19 Jan 2017 08:22

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