CAJ | 학술논문

针对红外图像弱小目标检测，提出了一种基于GCV小波阈值去噪的检测方法。先将图像进行小波多尺度分解以抑制杂波；然后利用GCV准则，对各个小波系数的子带图像分别进行阈值分割来抑制噪声；最后对降噪后的小波系数进行离散小波反变换，对重构后的图像进行二值分割从而得到最终检测结果。实验结果表明，与传统方法相比，该算法能够很好地抑制背景和噪声，并且对于重建图像能够更加准确地进行目标提取和分割。
침대홍외도상약소목표검측，제출료일충기우GCV소파역치거조적검측방법。선장도상진행소파다척도분해이억제잡파；연후이용GCV준칙，대각개소파계수적자대도상분별진행역치분할래억제조성；최후대강조후적소파계수진행리산소파반변환，대중구후적도상진행이치분할종이득도최종검측결과。실험결과표명，여전통방법상비，해산법능구흔호지억제배경화조성，병차대우중건도상능구경가준학지진행목표제취화분할。
Concerning dim small target detection from infrared image ,a new method based on gener -alized cross validation( GCV) wavelet threshold denoising is presented .Firstly, for an IR image , a wave-let multiscale decomposition method is used to suppress clutter .Then the GCV criteria is applied to calcu-late the GCV threshold for each subband and the images are segmented separately for denoising .Finally, inverse descret wavelet transform ( IDWT) method is used for denoised wavelet coefficients and the target is segmented from the reconstructed image .Experimental results show that the presented algorithm can suppress background and noise well , which detects and segments dim small targets efficiently from recon-structed image .