Document Type

Article

Language

eng

Publication Date

2003

Publisher

Optical Society of America

Source Publication

Applied Optics

Source ISSN

1045-9219

Abstract

What is to our knowledge a new scene-based algorithm for nonuniformity correction in infrared focal-plane array sensors has been developed. The technique is based on the inverse covariance form of the Kalman filter (KF), which has been reported previously and used in estimating the gain and bias of each detector in the array from scene data. The gain and the bias of each detector in the focal-plane array are assumed constant within a given sequence of frames, corresponding to a certain time and operational conditions, but they are allowed to randomly drift from one sequence to another following a discrete-time Gauss-Markov process. The inverse covariance form filter estimates the gain and the bias of each detector in the focal-plane array and optimally updates them as they drift in time. The estimation is performed with considerably higher computational efficiency than the equivalent KF. The ability of the algorithm in compensating for fixed-pattern noise in infrared imagery and in reducing the computational complexity is demonstrated by use of both simulated and real data.

Comments

Accepted version. Applied Optics, Vol. 42, No. 29 (2003): 5872-5881. DOI. © 2003 Optical Society of America. Used with permission.

Majeed M. Hayat was affiliated with Univesity of New Mexico, Albuquerque at the time of publication.

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