CAJ | 학술논문

该文提出了一种新的结合非下采样Contourlet变换(NSCT)和自适应全变差模型的图像去噪方法.首先通过NSCT对含噪图像进行分解,根据高斯比例混合(GSM)模型建立图像模型;然后利用贝叶斯估计进行图像去噪,重构后得到初次去噪图像;最后,结合自适应全变差模型对初次去噪图像进行重构滤波,得到最终的去噪图像.实验结果表明,该方法可以有效地消除图像中的Gibbs伪影及噪声,在去噪图像峰值信噪比(PSNR)和边缘保持性能上都优于已有的算法.
해문제출료일충신적결합비하채양Contourlet변환(NSCT)화자괄응전변차모형적도상거조방법.수선통과NSCT대함조도상진행분해,근거고사비례혼합(GSM)모형건립도상모형;연후이용패협사고계진행도상거조,중구후득도초차거조도상;최후,결합자괄응전변차모형대초차거조도상진행중구려파,득도최종적거조도상.실험결과표명,해방법가이유효지소제도상중적Gibbs위영급조성,재거조도상봉치신조비(PSNR)화변연보지성능상도우우이유적산법.
This paper presents a new image denoising scheme by combining the NonSubsampled Contourlet Transform (NSCT) and adaptive total variation model. The original image is first decomposed using NSCT and the image model is built based on Gaussian Scale Mixtures (GSM) model. Then the image noises are removed using Bayesian estimation, producing the preliminary denoised image after reconstruction. Then the preliminary primary denoised image is further filtered using the adaptive total variation model, producing the final denoised image. Experiments show that the proposed scheme can remove Gibbs-like artifacts and image noise effectively. Besides, it outperforms the existing schemes in regard of both the Peak-Signal-to-Noise-Ratio (PSNR) and the edge preservation ability.