A Bayesian approach to uncovered background and moving pixel detection

Author

Matthews, Kristine ; Namazi, Nader

Author_Institution

Dept. of Electr. Eng., Catholic Univ. of America, Washington, DC, USA

Volume

4

fYear

1995

fDate

9-12 May 1995

Firstpage

2245

Abstract

We have formulated and evaluated a binary hypothesis test for the detection of uncovered background pixels between image frames in a noisy image sequence where we assume additive, white, Gaussian noise. We have extended the binary hypothesis test to a 3-ary hypothesis test to allow for the segmentation of the image into three regions: uncovered background, stationary and moving pixels. We have evaluated both the binary and 3-ary hypothesis tests using a single measurement and multiple measurements for classifying each pixel on synthetic images, and we have evaluated the 3-ary hypothesis test on the Trevor image sequence

Keywords

Bayes methods; Gaussian noise; image classification; image sequences; motion estimation; white noise; 3-ary hypothesis test; Bayesian approach; additive white Gaussian noise; binary hypothesis test; image frames; image sequence; measurements; moving pixel detection; noisy image sequence; pixel classification; stationary pixels; synthetic images; uncovered background pixel detection; Additive noise; Additive white noise; Background noise; Bayesian methods; Gaussian noise; Image segmentation; Image sequences; Pixel; Testing; Writing;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 1995. ICASSP-95., 1995 International Conference on

Conference_Location

Detroit, MI

ISSN

1520-6149

Print_ISBN

0-7803-2431-5

Type

conf

DOI

10.1109/ICASSP.1995.479937

Filename

479937