CAJ | 학술논문

分析了传统神经网络非均匀性校正算法在空域处理过程中产生目标退化的原因,在总结基于边缘指导的神经网络校正算法(ED-NN-NUC)与一点定标和神经网络结合的校正算法的基础上,提出了新的组合校正算法.新算法包含预校正、粗校正和精校正三个处理模块,利用含有弱小目标的实际红外图像进行了实验验证.结果表明,新算法能有效地抑止目标退化,并在运算速度上比ED-NN-NUC有一定的提高.
분석료전통신경망락비균균성교정산법재공역처리과정중산생목표퇴화적원인,재총결기우변연지도적신경망락교정산법(ED-NN-NUC)여일점정표화신경망락결합적교정산법적기출상,제출료신적조합교정산법.신산법포함예교정、조교정화정교정삼개처리모괴,이용함유약소목표적실제홍외도상진행료실험험증.결과표명,신산법능유효지억지목표퇴화,병재운산속도상비ED-NN-NUC유일정적제고.
The cause of the target fade-out in the traditional neural network nonuniformity correction algorithms for infrared focal plane array(IRFPA)was studied. A new combinational algorithm for nonuniformity correction was proposed on the basis of analyzing the strengths and limitations of edge-directed NN scheme(ED-NN-NUC) and nonuniformity correction combining one-point calibration and NN-NUC. The new algorithm includes three modules which are pre-correction, rough correction and accurate correction. The real infrared image including dim targets was used to validate the proposed algorithm. The results show that the proposed algorithm can effectively eliminate the target fade-out, and it is less time consuming than ED-NN-NUC.