An algebraic restoration method for estimating fixed-pattern noise in infrared imagery from a video sequence

Unal Sakoglu; Russell C. Hardie; Majeed M. Hayat; Bradley M. Ratliff; J. Scott Tyo

doi:10.1117/12.557902

2 November 2004 An algebraic restoration method for estimating fixed-pattern noise in infrared imagery from a video sequence

Unal Sakoglu, Russell C. Hardie, Majeed M. Hayat, Bradley M. Ratliff, J. Scott Tyo

Author Affiliations +

Proceedings Volume 5558, Applications of Digital Image Processing XXVII; (2004) https://doi.org/10.1117/12.557902
Event: Optical Science and Technology, the SPIE 49th Annual Meeting, 2004, Denver, Colorado, United States

Abstract

The inherent nonuniformity in the photoresponse and readout-circuitry of the individual detectors in infrared focal-plane-array imagers result in the notorious fixed-pattern noise (FPN). FPN generally degrades the performance of infrared imagers and it is particularly problematic in the midwavelength and longwavelength infrared regimes. In many applications, employing signal-processing techniques to combat FPN may be preferred over hard calibration (e.g., two-point calibration), as they are less expensive and, more importantly, do not require halting the operation of the camera. In this paper, a new technique that uses knowledge of global motion in a video sequence to restore the true scene in the presence of FPN is introduced. In the proposed setting, the entire video sequence is regarded as an output of a motion-dependent linear transformation, which acts collectively on the true scene and the unknown bias elements (which represent the FPN) in each detector. The true scene is then estimated from the video sequence according to a minimum mean-square-error criterion. Two modes of operation are considered. First, we consider non-radiometric restoration, in which case the true scene is estimated by performing a regularized minimization, since the problem is ill-posed. The other mode of operation is radiometric, in which case we assume that only the perimeter detectors have been calibrated. This latter mode does not require regularization and therefore avoids compromising the radiometric accuracy of the restored scene. The algorithm is demonstrated through preliminary results from simulated and real infrared imagery.

Citation Download Citation

Unal Sakoglu, Russell C. Hardie, Majeed M. Hayat, Bradley M. Ratliff, and J. Scott Tyo "An algebraic restoration method for estimating fixed-pattern noise in infrared imagery from a video sequence", Proc. SPIE 5558, Applications of Digital Image Processing XXVII, (2 November 2004); https://doi.org/10.1117/12.557902

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available