CAJ | 학술논문

提出了一种新的基于粒子群优化粒子滤波(PSOPF)的红外目标提取算法,将红外目标提取阈值的计算问题看作系统状态估计问题.在粒子滤波的框架下,建立了关于灰度-方差加权信息熵和像素点灰度值的阈值状态空间,建立了基于粒子群优化算法思想的系统状态转移模型,建立了基于红外目标提取效果评价函数的系统观测模型,它有效综合了红外图像中灰度、信息熵、梯度、像素点的空间位置等信息.最后,以粒子的加权平均估计目标提取的阈值.实验结果表明,该方法是有效且稳健的.
제출료일충신적기우입자군우화입자려파(PSOPF)적홍외목표제취산법,장홍외목표제취역치적계산문제간작계통상태고계문제.재입자려파적광가하,건립료관우회도-방차가권신식적화상소점회도치적역치상태공간,건립료기우입자군우화산법사상적계통상태전이모형,건립료기우홍외목표제취효과평개함수적계통관측모형,타유효종합료홍외도상중회도、신식적、제도、상소점적공간위치등신식.최후,이입자적가권평균고계목표제취적역치.실험결과표명,해방법시유효차은건적.
A novel infrared target extraction algorithm based on particle swarm optimization particle filter (PSOPF) was proposed. The problem of infrared target extraction was analyzed and solved in the view of state estimation. In the framework of particle filter, the threshold state space on the gray-variance weighted information entropy and the gray value of each pixel was established. Particle swarm optimization was introduced to construct the state transition model. The observation model based on extraction results evaluation function was constructed, which integrated gray, entropy, gradient and spatial distribution of pixels. Finally, the weighted average of all the particles was used as target extraction threshold. The experiment results prove that the proposed algorithm is effective and robust.