The Artificial Neural Networks Technique Applied To The Nonuniformity Correction Of The Infrared Focal Plane Array

Infrared focal plane array(IRFPA) can be superior for infrared imaging systems not only because of its simplicity and compactness in structure ,but also because of its high sensitivity and low power depletion. And infrared focal plane array is applied to imaging system widely and attracted lots of attention. Unfortunately, its inherent nonuniformity can degrade image quality and system performance. Hence, nonunifbrmity correction(NUC) becomes necessary.The paper firstly describes the reasons of the nonuniformity in the IRFPA. Then several methods of nonuniformity correction(NUC) for IRFPA are analyzed and compared, which leads to that the adaptive correction scheme is the best for the IR imaging system. Following that, artificial neural networks correction technique-back propagation(BP) algorithm is discussed in detail. On the base of above analysis, the unitary BP algorithm is introduced, which has more adaptability than classical BP algorithm. Experiments were performed. The unitary BP algorithm's effectiveness and superiority were verified by simulation. At the end of this paper, the possibility of hardware-realization of the algorithm is validated.