光学精密工程2012，Vol.20Issue(5)：949-956,8.DOI:10.3788/OPE.20122005.0949
可调对比度目标源装置中对比度的标定
Calibration of contrast for adjustable contrast optical target equipment
摘要
Abstract
An adjustable contrast optical target equipment was constructed. After researching the rela-tionship between image contrast and optical contrast, a contrast calibration method by the improved Back Propagation(BP) neural network was proposed. Firstly, the BP neural network model was designed for calibrating the contrast. Then, by combining the Levenberg-Marquardt(LM) with Shrink-ing-Magnifying Approach, the BP neural network was improved to optimize the convergence speed and generalization ability. Finally, based on the experimental platform of the adjustable-contrast target, the image contrast was obtained by measured radiation data. Comparing with the traditional BP algorithm, the improved one has a better convergence speed and generalization ability. Its calibration accuracy has been improved by 100 times and by 10 times as compared with those of the traditional BP network and the steepest descent method, respectively. When the training times is to be only 2 876 times, the maximum error between calibration value and target calibration value for the contrast is 0.01%, the training mean square error converges is 0. 000 459 441, and the test error converges is 0. 000 467 003. These results demonstrate that the algorithm is feasible and can meet the demands for contrast calibration in the equipment.关键词
可调目标源/对比度标定/LM算法/缩放法/神经网络Key words
adjustable target/ contrast calibration/ Levenberg-Marquart (LM) algorithm/ shrinking-magnif-ying approach/ neural network分类
通用工业技术引用本文复制引用
王素华,沈湘衡,叶露..可调对比度目标源装置中对比度的标定[J].光学精密工程,2012,20(5):949-956,8.基金项目
中国科学院创新基金资助项目(No.YZ200904) （No.YZ200904）
