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Recursive algorithms for bias and gain nonuniformity correction in infrared videos.
Pipa, Daniel R; da Silva, Eduardo A B; Pagliari, Carla L; Diniz, Paulo S R.
Afiliación
  • Pipa DR; Universidade Federal do Rio de Janeiro, Rio de Janeiro 21945-970, Brazil. danielpipa@ieee.org
IEEE Trans Image Process ; 21(12): 4758-69, 2012 Dec.
Article en En | MEDLINE | ID: mdl-22997263
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.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Grabación en Video / Algoritmos / Procesamiento de Imagen Asistido por Computador / Rayos Infrarrojos Límite: Humans Idioma: En Revista: IEEE Trans Image Process Asunto de la revista: INFORMATICA MEDICA Año: 2012 Tipo del documento: Article País de afiliación: Brasil Pais de publicación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Grabación en Video / Algoritmos / Procesamiento de Imagen Asistido por Computador / Rayos Infrarrojos Límite: Humans Idioma: En Revista: IEEE Trans Image Process Asunto de la revista: INFORMATICA MEDICA Año: 2012 Tipo del documento: Article País de afiliación: Brasil Pais de publicación: Estados Unidos