Detecting boundaries in a vector field

Author

Lee, Hsien-Che ; Cok, David R.

Author_Institution

Eastman Kodak Co., Rochester, NY, USA

Volume

39

Issue

5

fYear

1991

fDate

5/1/1991 12:00:00 AM

Firstpage

1181

Lastpage

1194

Abstract

A vector gradient approach is proposed to detect boundaries in multidimensional data with multiple attributes (a vector field). It is used to extend a gradient edge detector to color images. The statistical effects of noise on the distribution of the amplitudes and directions of the vector gradient are characterized. The noise behavior of the L ₂ norm of the scalar gradients is also characterized for comparison. When the attribute components are highly correlated, as is often the case in color images, use of the vector gradient shows a small gain in signal-to-noise ratio over that of the L₂ norm of the scalar gradients. This small gain may or may not be significant, depending on other measures an edge detector uses to deal with noise

Keywords

pattern recognition; picture processing; white noise; boundary detection; color images; gradient edge detector; multidimensional data; signal-to-noise ratio; statistical effects; vector field; vector gradient amplitudes; vector gradient approach; vector gradient directions; white Gaussian noise; Color; Colored noise; Detectors; Gain measurement; Image edge detection; Magnetic resonance imaging; Multidimensional systems; Noise level; Noise measurement; Signal to noise ratio;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/78.80971

Filename

80971