DocumentCode :
1988248
Title :
Anisotropic diffusion processes in early vision
Author :
Perona, P.
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., California Univ., Berkeley, CA, USA
fYear :
1989
fDate :
6-8 Sep 1989
Firstpage :
68
Abstract :
Summary form only given. Images often contain information at a number of different scales of resolution, so that the definition and generation of a good scale space is a key step in early vision. A scale space in which object boundaries are respected and smoothing only takes place within these boundaries has been defined that avoids the inaccuracies introduced by the usual method of low-pass-filtering the image with Gaussian kernels. The new scale space is generated by solving a nonlinear diffusion differential equation forward in time (the scale parameter). The original image is used as the initial condition, and the conduction coefficient c(x, y, t) varies in space and scale as a function of the gradient of the variable of interest (e.g. the image brightness). The algorithms are based on comparing the local values of different diffusion processes running in parallel on the same image
Keywords :
picture processing; algorithms; analog networks; anisotropic diffusion process; conduction coefficient; digital architectures; early vision; edge detection; gradient; image brightness; image compression; initial condition; nonlinear diffusion differential equation; object boundaries; parallel computation structure; scale space; Anisotropic magnetoresistance; Brightness; Diffusion processes; Filtering; Image analysis; Image edge detection; Image resolution; Kernel; Low pass filters; Performance analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Multidimensional Signal Processing Workshop, 1989., Sixth
Conference_Location :
Pacific Grove, CA
Type :
conf
DOI :
10.1109/MDSP.1989.97028
Filename :
97028
Link To Document :
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