CAJ | 학술논문

红外焦平面探测器的非均匀性校正技术仍然是当前红外热成像系统重点研究的关键技术之一。相对定标类算法，基于场景非均匀性校正根据场景进行非均匀参数更新，不需要使用挡板遮挡视场。本文介绍传统神经网络非均匀性校正算法及加快收敛速度的改进措施，引入边缘检测方法来克服传统神经网络算法的鬼影问题。文中阐述的方法已在以TMS320DM643为处理核心DSP硬件处理平台上实现，取得了较好的校正效果。
홍외초평면탐측기적비균균성교정기술잉연시당전홍외열성상계통중점연구적관건기술지일。상대정표류산법，기우장경비균균성교정근거장경진행비균균삼수경신，불수요사용당판차당시장。본문개소전통신경망락비균균성교정산법급가쾌수렴속도적개진조시，인입변연검측방법래극복전통신경망락산법적귀영문제。문중천술적방법이재이TMS320DM643위처리핵심DSP경건처리평태상실현，취득료교호적교정효과。
The Fixed Pattern Noise (FPN) of the infrared focal plane array severely limits the system performance, and the non-uniformity correction algorithm is a key technique of thermal imaging system. The scene-based non-uniformity correction algorithm does not require a shutter to block the field of view, but utilizes the scene information of image sequences to calculate the infrared focal plane array non-uniformity parameters. This paper introduces an improved neural network non-uniformity correction algorithm, which speeds up the convergence rate of the conventional neural network algorithm. The improved algorithm employs the edge detection method to overcome the ghosting artifacts generated by the conventional algorithm. The algorithm has run on a small low power consumption DSP hardware platform with TMS320DM643 as the kernel processor and can do the correction in a simple way with satisfactory results, so the algorithm introduced in this paper is proved to be reasonable and effective.