Sergio N. Torres

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A novel statistical approach is undertaken for the adaptive estimation of the gain and bias nonuniformity in infrared focal-plane array sensors from scene data. The gain and the bias of each detector are regarded as random state variables modeled by a discrete-time Gauss-Markov process. The proposed Gauss-Markov framework provides a mechanism for capturing(More)
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(More)
We present an adaptive technique for the estimation of nonuniformity parameters of infrared focal-plane arrays that is robust with respect to changes and uncertainties in scene and sensor characteristics. The proposed algorithm is based on using a bank of Kalman filters in parallel. Each filter independently estimates state variables comprising the gain and(More)
A novel adaptive scene-based nonuniformity correction technique is presented. The technique simultaneously estimates detector parameters and performs the nonuniformity correction based on the retina-like neural network approach. The proposed method includes the use of an adaptive learning rate rule in the gain and offset parameter estimation process. This(More)
Topic: Signal Processing and Analysis. Abstract. A statistical technique for adaptive nonuniformity correction of infrared image sequences has been developed. The method, which relies on our previously developed constant range nonuniformity correction method, estimates the nonuniformity parameters using two recur-sive estimation techniques. The method(More)
The non-uniform response in infrared focal plane array (IRFPA) detectors produces corrupted images with a fixed-pattern noise. In this paper we present a new adaptive scene-based non-uniformity correction (NUC) technique. The method simultaneously estimates detector's parameters and performs the non-uniformity compensation using a neural approach and a(More)
In this paper, a technique to improve the convergence and to reduce the ghosting artifacts of a previously developed adaptive scene-based nonuniformity correction method is presented. The nonuniformity correction method estimates detector parameters based on the recur-sive least square filter approach. We propose, three parameters to reduce ghosting(More)