IEEE Trans Image Process - Recursive algorithms for bias and gain nonuniformity correction in infrared videos.

Tópicos

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Resumo

Infrared focal-plane array (IRFPA) detectors suffer from fixed-pattern noise (FPN) that degrades image quality, which is also known as spatial nonuniformity. FPN is still a serious problem, despite recent advances in IRFPA technology. This paper proposes new scene-based correction algorithms for continuous compensation of bias and gain nonuniformity in FPA sensors. The proposed schemes use recursive least-square and affine projection techniques that jointly compensate for both the bias and gain of each image pixel, presenting rapid convergence and robustness to noise. The synthetic and real IRFPA videos experimentally show that the proposed solutions are competitive with the state-of-the-art in FPN reduction, by presenting recovered images with higher fidelity.

Resumo Limpo

infrar focalplan array irfpa detector suffer fixedpattern nois fpn degrad imag qualiti also known spatial nonuniform fpn still serious problem despit recent advanc irfpa technolog paper propos new scenebas correct algorithm continu compens bias gain nonuniform fpa sensor propos scheme use recurs leastsquar affin project techniqu joint compens bias gain imag pixel present rapid converg robust nois synthet real irfpa video experiment show propos solut competit stateoftheart fpn reduct present recov imag higher fidel

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