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由美国夜视和电子传感器管理局(NVESD)研究提出的经典视场目标探测模型,未能反映出信杂比(SCR)在探测过程中的影响程度。采用小波多尺度边缘检测法来仿效视觉系统,将边缘概率(POE)与经小波多分辨分析法改造后的雷诺一致性方程的均方根(RMS)结合,得到基于小波多尺度POE算法。再利用最大似然法对目标和背景分类探测进行处理,从而获得目标模式识别的最大似然概率;将信杂比计算引入红外目标探测中,推导出了高、中、低信杂比下的目标探测、分类和识别预测方法,解决了红外目标探测过程中与信杂比的关系。
The classic field of view target detection model proposed by the NVESD failed to show the influence of signal to noise ratio (SCR) on the detection process. The wavelet multiscale edge detection method is used to imitate the visual system, and the edge probability (POE) is combined with the root mean square (RMS) of the Renault’s consistency equation after the wavelet multiresolution analysis is modified to obtain the wavelet multi-scale POE algorithm. Then the maximum likelihood method is used to deal with the target and background classification detection to obtain the maximum likelihood probability of target pattern recognition. The signal-to-noise ratio calculation is introduced into the infrared target detection to derive the high, medium and low SNR Target detection, classification and identification of prediction methods to solve the infrared target detection process and the relationship between signal to noise ratio.