Title :
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
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;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1995. ICASSP-95., 1995 International Conference on
Conference_Location :
Detroit, MI
Print_ISBN :
0-7803-2431-5
DOI :
10.1109/ICASSP.1995.479937
