CAJ | 학술논문

本文提出了一种基于形态学和小波域杂波抑制的微弱目标检测方法,该方法将图像序列进行形态擘tophat滤波,然后小波变换,再分别对各小波子带作平滑滤波,按各子带对滤波前后小波系数作差分运算,最后经过小波逆变换得到具有微弱目标的残差图像序列.用残差图像tophat结果估计目标潜在区域,在目标潜在域的约束下,对残差图像序列进行时空域数据融合,实现微弱运动目标的检测.仿真实验表明,该方法杂波抑制后残差图像具有很好的白高斯特性,且目标邻域信杂比(scNR)的平均增益比图像空域平滑滤波和图像频域低通滤波等典型运算的SCNR平均增益有明显改善,目标检测算法在5帧图像集成时能稳定检测出微弱运动目标轨迹.
본문제출료일충기우형태학화소파역잡파억제적미약목표검측방법,해방법장도상서렬진행형태벽tophat려파,연후소파변환,재분별대각소파자대작평활려파,안각자대대려파전후소파계수작차분운산,최후경과소파역변환득도구유미약목표적잔차도상서렬.용잔차도상tophat결과고계목표잠재구역,재목표잠재역적약속하,대잔차도상서렬진행시공역수거융합,실현미약운동목표적검측.방진실험표명,해방법잡파억제후잔차도상구유흔호적백고사특성,차목표린역신잡비(scNR)적평균증익비도상공역평활려파화도상빈역저통려파등전형운산적SCNR평균증익유명현개선,목표검측산법재5정도상집성시능은정검측출미약운동목표궤적.
The method of dim target detection based on spatio-morphological and wavelet transform clutter suppression is proposed. The image sequences are processed with spatial tophat filtering. The results are transformed into wavelet domain, and filtered by smooth filter in every wavelet belt, and the difference process is operated between the pre-andafter filtering coefficients. The inverse wavelet transform is carried out to produce the residue image sequences with dim targets. The tophat filtered image is used to estimate the possible target support area. Under the restriction of the possible target area, the tempo-spatial data fusion is performed to detect the trajectories of dim targets. Simulation results show that the obtained residual images have very good white Gaussian normality, and the average gain of the target's neighborhood Signal-to-clutter-noise Ratio (SCNR) can be improved obviously compared with traditional image smooth filtering and frequency filtering algorithms. The trajectories of dim targets can be detected steadily with 5 image frames.