Title :
Recursive estimation techniques for detection of small objects in infrared image data
Author :
Soni, Tarun ; Zeidler, J. ; Ku, Walter H.
Author_Institution :
Dept. of Electr. & Comput. Eng., California Univ., San Diego, La Jolla, CA, USA
Abstract :
A recursive detection scheme for point targets in infrared images is described. Estimation of the background noise is done using a weighted autocorrelation matrix update method and the detection statistic is calculated using a recursive technique. A weighting factor allows the algorithm to have finite memory and deal with nonstationary noise characteristics. The detection statistic is created by using a matched filter for colored noise, using the estimated noise autocorrelation matrix. The relationship between the weighting factor, the nonstationarity of the noise and the probability of detection is described. Some results on one- and two-dimensional infrared images are presented
Keywords :
filtering and prediction theory; infrared imaging; matched filters; noise; signal detection; 1D images; 2D images; IR images; background noise; colored noise; detection probability; detection statistic; infrared images; matched filter; nonstationary noise; point targets; recursive estimation techniques; small objects detection; weighted autocorrelation matrix update method; weighting factor; Autocorrelation; Background noise; Colored noise; Infrared detectors; Infrared imaging; Matched filters; Object detection; Probability; Recursive estimation; Statistics;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1992. ICASSP-92., 1992 IEEE International Conference on
Conference_Location :
San Francisco, CA
Print_ISBN :
0-7803-0532-9
DOI :
10.1109/ICASSP.1992.226146
