Abstract

A statistical algorithm has been developed to compensate for the fixed-pattern noise associated with spatial nonuniformity and temporal drift in the response of focal-plane array infrared imaging systems. The algorithm uses initial scene data to generate initial estimates of the gain, the offset, and the variance of the additive electronic noise of each detector element. The algorithm then updates these parameters by use of subsequent frames and uses the updated parameters to restore the true image by use of a least-mean-square error finite-impulse-response filter. The algorithm is applied to infrared data, and the restored images compare favorably with those restored by use of a multiple-point calibration technique.

© 1999 Optical Society of America

An algebraic algorithm for nonuniformity correction in focal-plane arrays

Bradley M. Ratliff, Majeed M. Hayat, and Russell C. Hardie
J. Opt. Soc. Am. A 19(9) 1737-1747 (2002)

Noise-cancellation-based nonuniformity correction algorithm for infrared focal-plane arrays

Sebastián E. Godoy, Jorge E. Pezoa, and Sergio N. Torres
Appl. Opt. 47(29) 5394-5399 (2008)

Scene-based nonuniformity correction technique for infrared focal-plane arrays

Yong-Jin Liu, Hong Zhu, and Yi-Gong Zhao
Appl. Opt. 48(12) 2364-2372 (2009)

Scene-based nonuniformity correction technique that exploits knowledge of the focal-plane array readout architecture

Balaji Narayanan, Russell C. Hardie, and Robert A. Muse
Appl. Opt. 44(17) 3482-3491 (2005)

Kalman filtering for adaptive nonuniformity correction in infrared focal-plane arrays

Sergio N. Torres and Majeed M. Hayat
J. Opt. Soc. Am. A 20(3) 470-480 (2003)