relation: https://khub.utp.edu.my/scholars/1887/
title: Noise reduction using mean shift algorithm for estimating 3D shape
creator: Shim, S.-O.
creator: Malik, A.S.
creator: Choi, T.-S.
description: 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 minimising 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. © RPS 2011.
date: 2011
type: Article
type: PeerReviewed
identifier:   Shim, S.-O. and Malik, A.S. and Choi, T.-S.  (2011) Noise reduction using mean shift algorithm for estimating 3D shape.  Imaging Science Journal, 59 (5).  pp. 267-273.  ISSN 13682199     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-80051769917&doi=10.1179%2f136821910X12867873897553&partnerID=40&md5=1abc60cc665bdcd794aaf05aebcf91c7
relation: 10.1179/136821910X12867873897553
identifier: 10.1179/136821910X12867873897553