CAJ | 학술논문

提出一种基于Contourlet变换域的图像滤噪算法,对带噪图像进行多尺度、多方向的Contourlet分解,依据Contourlet变换域系数的估计损失期望最小化准则,在Contourlet域中得到各子带内邻域系数的滤噪最优阈值与最优窗口尺寸,利用Contourlet变换域系数的萎缩实现滤噪.仿真结果表明,与现有的Contourlet变换域图像滤噪算法相比,该算法能有效保护图像的细节和纹理,具有较好的视觉效果和较高的峰值信噪比.
제출일충기우Contourlet변환역적도상려조산법,대대조도상진행다척도、다방향적Contourlet분해,의거Contourlet변환역계수적고계손실기망최소화준칙,재Contourlet역중득도각자대내린역계수적려조최우역치여최우창구척촌,이용Contourlet변환역계수적위축실현려조.방진결과표명,여현유적Contourlet변환역도상려조산법상비,해산법능유효보호도상적세절화문리,구유교호적시각효과화교고적봉치신조비.
This paper proposes a novel image danoising algorithm based on Contourlet domain.By using Contourlet transform,the noised image is decomposed into a low frequency subband and a set of multiscale and multidirectional high frequency subbands.Optimal thresholds and neighbouring window sizes for each subband are determined by minimizing the loss expectation of estimating Contourlet coefficients and image denoising is implemented via shrinkage of Contourlet coefficients.Simulation results show the superiority of the proposed method in denoising noise and preserving texture details compared with the existing methods and the proposed method yields better visual effect and higher PSNR as a result of considering dependencies of Contourlet neighborhood coefficients.