CAJ | 학술논문

为提高红外图像拼接速度和精度，对基于特征点匹配的图像拼接算法进行改进。根据图像空间特性减小角点搜索范围，通过设定梯度阈值，对梯度超过阈值的像素点进行Harris角点检测；改进Harris角点响应函数和角点筛选阈值的设定方式，摆脱了角点检测对筛选经验值的依赖。在相似测度Normalized Cross Correlation （NCC）粗匹配的基础上，采用有约束条件的随机选取方式，增强子集选取的合理性；并根据先局部后整体的匹配策略，基于匹配点的特性进行预检验，降低匹配错误率。算法最后利用最优变换矩阵确定待拼接图像的位置关系，实现自动拼接。实验结果表明，改进后算法在拼接过程中无需人工干预，在保证红外图像拼接质量的基础上，拼接速度提高了65．92％。
위제고홍외도상병접속도화정도，대기우특정점필배적도상병접산법진행개진。근거도상공간특성감소각점수색범위，통과설정제도역치，대제도초과역치적상소점진행Harris각점검측；개진Harris각점향응함수화각점사선역치적설정방식，파탈료각점검측대사선경험치적의뢰。재상사측도Normalized Cross Correlation （NCC）조필배적기출상，채용유약속조건적수궤선취방식，증강자집선취적합이성；병근거선국부후정체적필배책략，기우필배점적특성진행예검험，강저필배착오솔。산법최후이용최우변환구진학정대병접도상적위치관계，실현자동병접。실험결과표명，개진후산법재병접과정중무수인공간예，재보증홍외도상병접질량적기출상，병접속도제고료65．92％。
In order to improve the speed and the accuracy of infrared image mosaicing,we made an improvement on the feature point matching-based image mosaicing algorithm.The scanning range of the corner detection was narrowed according to the spatial feature of the image,and by setting the gradient threshold,Harris corner detection was applied to those pixel points with gradient exceeding the threshold;The Harris corner responding function and the setting way of corner screening threshold were improved,this get rid of the dependence of corner detection on screening experience value.Based on similarity metric NCC (normalised cross correlation)coarse matching,we adopted the constraint random selection means to enhance the rationality of subset selection;and according to local-to-global matching strategy we made pre-detection based on the features of matching points to lower the matching error rate.At last the algorithm used the optimal transformation matrix to determine the position relationships between images under mosaicing,thus realised auto-mosaicing.Experimental results showed that the improved algorithm did not need artificial intervention in mosaicing process,the mosaicing speed increased by 65 .92%on the basis of ensuring the quality of infrared images mosaicing.