An Improved Non-uniformity Correction Algorithm for IRFPA Based on Neural Network

スポンサーリンク

概要

• 論文の詳細を見る

• Aiming at traditional neural networks non-uniformity correction (NUC) algorithms disadvantages such as slow convergence, low correction precision and difficulty to meet the real-time engineering application requirements of infrared imaging system, an improved NUC algorithm for infrared focal plane arrays (IRFPA) based on neural network is proposed. The algorithm is based on linear response of detector, and in order to realize fast and synchronization convergence of correction parameters the each original image data is normalized to a value close to one. Experimental results show the method has the faster convergence speed and better vision effect than the traditional algorithms, and it is better applied in practical projects.

• （社）電子情報通信学会の論文
• 2009-05-01

著者

• Zhang Tian-qi

  Institute Of Signal Processing And Soc School Of Communication And Information Engineering Chongqing

• DAI Shao-sheng

  Institute of Signal Processing and SOC, School of Communication and Information Engineering, Chongqi

• Dai Shao-sheng

  Institute Of Signal Processing And Soc School Of Communication And Information Engineering Chongqing

関連論文

• An Improved Non-uniformity Correction Algorithm for IRFPA Based on Neural Network
• A Nonlinear Piecewise Scheme for Non-uniformity Correction in IRFPA

スポンサーリンク