%X The objective of the 3D shape estimation from focus is to estimate depth map of the scene or object based on best focus points from camera lens. In shape from focus (SFF), the measure of focus - sharpness - is the crucial part for final 3D shape estimation. However the noise imposed during image acquisition process by imaging system prevents exact focus measure. The traditional noise filters remove not only noise but also sharpness information. In this paper, mean shift algorithm was applied to remove noise imposed by the imaging process while minimizing loss of informative edges. Experimental results show that the mean shift algorithm can be applied before computing focus measure from image sequence corrupted by Gaussian noise and Impulse noise. Applying mean shift filtering before computing focus measure is promising in case the noise type during image acquisition is not known. © 2010 Copyright SPIE - The International Society for Optical Engineering.
%O cited By 3; Conference of 2nd International Conference on Digital Image Processing ; Conference Date: 26 February 2010 Through 28 February 2010; Conference Code:79521
%J Proceedings of SPIE - The International Society for Optical Engineering
%D 2010
%L scholars1282
%T Pre-processing for noise reduction in depth estimation
%A S.-O. Shim
%A A.S. Malik
%A T.-S. Choi
%C Singapore
%V 7546
%K 3DShape recovery; Depth from focus; Depth Map; Focus measure; Mean shift; Noise reductions; Shape from focus, Acoustic noise measurement; Digital image storage; Edge detection; Estimation; Gaussian noise (electronic); Image acquisition; Image sensors; Imaging systems; Impulse noise; Optoelectronic devices; Shape optimization; Vector quantization, Three dimensional
%R 10.1117/12.853050