Implementation Scheme for Recursion in Spectral Dimension
Final rept. Sep 1990-Mar 1991,
MARYLAND UNIV BALTIMORE COUNTY CATONSVILLE DEPT OF ELECTRICAL ENGINEERING
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Developing recursive detection algorithms for thermal image processing is very important for real time implementation. In his previous work for CRDEC, Warren used a first order autoregressive time series to model the background of thermal image with which he further developed a recursive algorithm in time frames. In this report, we revisit his work and present an alternative approach to developing a recursive algorithm for thermal image target detection. The new approach uses Kalman filter theory, which has proven to be very powerful in real time processing because of its recursive nature. The algorithm developed by Warren is designed for a single spectral band. In reality, however, the characteristics of the vapor cloud and background may vary from band to band in spectral domain thus, it is practical to extend Warrens and the Kalman filtering approaches to cover multiple spectral bands. To alleviate the difficulty of processing multiple bands, two suboptimal models separable spectral correlation and separable spectral-Markov spatial correlation are also proposed for the background.
- Infrared Detection and Detectors