Open AccessNonuniformity Correction Design and Implementation for Infrared Image Based on FPGA and Artificial Neural Networks
Author(s) -
YuYang JunLu
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1693/1/012177
Subject(s) - field programmable gate array , artificial neural network , infrared , computer science , detector , calibration , focal plane arrays , artificial intelligence , infrared detector , computer vision , computer hardware , optics , mathematics , physics , telecommunications , statistics
Infrared imaging technology is widely used in military and civilian applications. However, due to the materials and manufacturing technology, the response of each unit in the infrared detector is not completely consistent, which leads to the nonuniformity of the infrared focal plane array. In this article, we propose a way to use artificial neural network by self-adaptively updating the correction coefficients based on FPGA. Compared with traditional calibration-based method, our method is more flexible and can avoid the effects of temperature drift efficiently.