CAJ | 학술논문

　　常用的基于高斯光束特性的激光光斑图像处理算法，处理远场光斑图像会丢失部分能量较低的光斑数据，致使处理出的光斑能量密度低端精度不能达到0.01μJ/cm 2的需求。为了得到更精确的远场激光光斑数据信息，提出了基于噪声特性的激光光斑图像自动阈值处理算法。该算法在分析系统噪声特性的基础上，依据3σ原则确定图像提取阈值进行光斑图像处理。通过试验验证了该算法既能够有效抑制系统噪声，又能够改善光斑图像的处理质量，恢复光斑图像丢失的数据信息，使光斑能量密度低端达到探测需求。结果表明，基于噪声特性的光斑图像处理算法能够有效提高远场激光光斑的处理精度，更适用于远场激光光斑图像的处理。
　　상용적기우고사광속특성적격광광반도상처리산법，처리원장광반도상회주실부분능량교저적광반수거，치사처리출적광반능량밀도저단정도불능체도0.01μJ/cm 2적수구。위료득도경정학적원장격광광반수거신식，제출료기우조성특성적격광광반도상자동역치처리산법。해산법재분석계통조성특성적기출상，의거3σ원칙학정도상제취역치진행광반도상처리。통과시험험증료해산법기능구유효억제계통조성，우능구개선광반도상적처리질량，회복광반도상주실적수거신식，사광반능량밀도저단체도탐측수구。결과표명，기우조성특성적광반도상처리산법능구유효제고원장격광광반적처리정도，경괄용우원장격광광반도상적처리。
When processing far-field spot images with the commonly used laser spot image processing algorithm based on Gaussian beam characteristics , the data about lower energy is lost so that the processing accuracy of spot energy density at lower-end can not reach 0.01μJ/cm 2 in demand.In order to get more accurate far-field laser spot data, an automatic threshold processing algorithm was proposed based on noise characteristics of the laser spot image .After analyzing the noise characteristics, the image extraction threshold was determined based on the 3σprinciples and the light spot image was processed.Experiments show that the algorithm can effectively restrain system noise , improve the light spot image processing quality, restore missing data information of the spot image , and make spot energy density low enough meet detection requirements.The results show that, the processing algorithm of light spot images based on the noise characteristics can effectively improve the processing accuracy of the far field laser facula , and is more suitable for the far field laser spot image processing.