摘要
为获得良好的红外焦平面阵列非均匀校正效果,讨论了非均匀性的来源、噪声类型和目前基于定标、基于场景的常用非均匀校正方法。对修正的时域高通滤波、改进的神经元网络等利用场景信息来估计探测器参数的校正算法进行了仿真效果和实时性能的分析与评价。同时设计了一种以TMS320DM642为处理核心的小型低功耗DSP硬件系统平台,描述了系统流程和实时实现策略,为红外焦平面系统提供了一条有效的实现路径。
In order to get good results of Nonuniformity Correction （NUC） of Infrared Focal Plane Arrays （IRFPA）, we discuss the origin of nonuniformity and types of noise generated by IRFPA imaging system, And the common methods of calibration-based and scene-based NUC are presented, The effects of simulation and real-time performance of two NUC approaches, modified temporal high-pass filtering and improved neural network, which use scene information captured by the imaging system to estimate the parameters of the detectors in some ways, are evaluated, At the same time, a small low power consumption DSP hardware platform with TMS320DM642 as the kernel processor is designed, The work flow of the system and the strategy of real-time realization are introduced. It is an effective choice for IRFPA.
出处
《光电工程》
EI
CAS
CSCD
北大核心
2007年第9期97-102,共6页
Opto-Electronic Engineering
基金
973项目支持
关键词
非均匀校正
红外焦平面阵列
红外技术
图像处理
nonuniformity correction
infrared focal plane arrays
infrared techniques
image processing
