Abstract
A new model (called multi-component blurring or MCB) to account for image blurring effects due to depth discontinuities is presented. We show that blurring processes operating in the vicinity of large depth discontinuities can give rise to emergent image details, quite distinguishable but nevertheless un-explained by previously available blurring models. In other words, the maximum principle for scale space [Per90] does not hold. It is argued that blurring in high-relief 3-D scenes should be more accurately modeled as a multi-component process. We present results form extensive and carefully designed experiments, with many images of real scenes taken by a CCD camera with typical parameters. These results have consistently support our new blurring model. Due care was taken to ensure that the image phenomena observed are mainly due to de-focussing and not due to mutual illuminations [For89], specularity [Hea87], objects' “finer” structures, coherent diffraction, or incidental image noises. [Gla88] We also hypothesize on the role of blurring on human depth-from-blur perception, based on correlation with recent results from human blur perception. [Hes89]
Keywords
This work is supported by the National Science Foundation under the Creativity in Engineering Award EID-8811553, and grant IRI-89-02728.
Download to read the full chapter text
Chapter PDF
References
Chen, Y. C., “Synthetic Image Generation for Highly Defocused Scenes”, Recent Advances in Computer Graphics, Springer-Verlag, 1988, pp. 117–125.
Ens, J., and Lawrence, P., “A Matrix Based Method for Determining Depth from Focus”, Proc. Computer Vision and Pattern Recognition 1991, pp. 600–606.
Forsyth, D., and Zisserman, A., “Mutual Illuminations”, Proc. Computer Vision and Pattern Recognition, 1989, California, USA, pp. 466–473.
Frieden, B., “Optical Transfer of Three Dimensional Object”, Journal of the Optical Society of America, Vol. 57, No. 1, 1967, pp. 56–66.
Garibotto, G. and Storace, P. “3-D Range Estimate from the Focus Sharpness of Edges”, Proc. of the 4th Intl. Conf. on Image Analysis and Processing (1987), Palermo, Italy, Vol. 2, pp. 321–328.
Ghatak, A. and Thyagarajan, K., Contemporary Optics, Plenum Press, New York, 1978.
Glasser, J., Vaillant, J., Chazallet, F., “An Accurate Method for Measuring the Spatial Resolution of Integrated Image Sensor”, Proc. SPIE Vol. 1027 Image Processing II, 1988, pp. 40–47.
Grossman, P., “Depth from Focus”, Pattern Recognition Letters, 5, 1987, pp. 63–69.
Healey, G. and Bindford, T., “Local Shape from Specularity”, Proc. of the 1st Intl. Conf. on Computer Vision (ICCV'87), London, UK, (1987), pp. 151–160.
Hess, R. F., Pointer, J. S., and R. J. Watt, “How are spatial filters used in fovea and parafovea?”, Journal of the Optical Society of America, A/Vol. 6, No. 2, Feb. 1989, pp. 329–339.
Hummel, R., Kimia, B. and Zucker, S., “Gaussian Blur and the Heat Equation: Forward and Inverse Solution”, Proc. Computer Vision and Pattern Recognition, 1985, pp. 668–671.
Krotkov, E. P., Active Computer Vision by Cooperative Focus and Stereo, Springer-Verlag, 1989, pp. 19–41.
Levine, M., Vision in Man and Machine, McGraw-Hill, 1985, pp. 220–224.
Nguyen, T. C., and Huang, T. S., Image Blurring Effects Due to Depth Discontinuities”, Technical Note ISP-1080, University of Illinois, May 1990.
Nguyen, T. C., and Huang, T. S., “Image Blurring Effects Due to Depth Discontinuities”, Proc. Image Understanding Workshop, 1990, pp. 174–178.
Perona, P. and Malik, J., “Scale-space and Edge Detection using Anisotropic Diffusion”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. PAMI-12, No. 7, July 1990, pp. 629–639.
Pentland, A., “A New Sense for Depth of Field”, IEEE Trans. on Pattern Recognition and Machine Intelligence, Vol. PAMI-9, No. 4 (1987), pp. 523–531.
Pentland, A., Darrell, T., Turk, M., and Huang, W., “A Simple, Real-time Range Camera”, Proc. Computer Vision and Pattern Recognition, 1989, pp. 256–261.
Subbarao, M., “Parallel Depth Recovery by Changing Camera Parameters, Proc. of the 2nd Intl. Conf. on Computer Vision, 1988, pp. 149–155.
Subbarao, M., “Parallel Depth Recovery from Blurred Edges”, Proc. Computer Vision and Pattern Recognition, Ann Arbor, June 1988, pp. 498–503.
Texas Instruments Inc., Advanced Information Document for TI Imaging Sensor TC241, Texas, August 1986.
Watt, R. J., and Morgan M. J., “The Recognition and Representation of Edge Blur: Evidence for Spatial Primitives in Human Vision”, Vision Research, Vol. 23, No. 12, 1983, pp. 1465–1477.
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 1992 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Nguyen, T.C., Huang, T.S. (1992). Image blurring effects due to depth discontinuitites: Blurring that creates emergent image details. In: Sandini, G. (eds) Computer Vision — ECCV'92. ECCV 1992. Lecture Notes in Computer Science, vol 588. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-55426-2_39
Download citation
DOI: https://doi.org/10.1007/3-540-55426-2_39
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-55426-4
Online ISBN: 978-3-540-47069-4
eBook Packages: Springer Book Archive