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Proceedings Paper

Noise sensitivity analysis of depth-from-defocus by a spatial-domain approach
Author(s): Murali Subbarao; JennKwei Tyan
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Paper Abstract

Depth-from-Defocus using the Spatial-Domain Convolution/Deconvolution Transform Method (STM) is a useful technique for 3D vision. STM involves simple local operations in the spatial domain on only two images recorded with different camera parameters (e.g. by changing lens position or changing aperture diameter). In this paper we provide a theoretical treatment of the noise sensitivity analysis of STM and verify the theoretical results with experiments. This fills an important gap in the current research literature wherein the noise sensitivity analysis of STM is limited to experimental observations. Given the image and noise characteristics, here we derive an expression for the Root Mean Square (RMS) error in lens position for focusing an object. This RMS error is useful in estimating the uncertainty in depth obtained by STM. We present the results of computer simulation experiments for different noise levels. The experiments validate the theoretical results.

Paper Details

Date Published: 7 July 1997
PDF: 14 pages
Proc. SPIE 3174, Videometrics V, (7 July 1997); doi: 10.1117/12.279778
Show Author Affiliations
Murali Subbarao, SUNY/Stony Brook (United States)
JennKwei Tyan, SUNY/Stony Brook (United States)


Published in SPIE Proceedings Vol. 3174:
Videometrics V
Sabry F. El-Hakim, Editor(s)

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