CAJ | 학술논문

针对小波域比例萎缩降噪方法在去除噪声的同时也弱化了图像细节和边缘的缺陷,提出了具有增强效果的基于最大后验概率准则的小波域自适应降噪算法,并将之应用于红外图像降噪中.该算法在假定图像系数和噪声系数先验为高斯分布的基础上,利用最大后验概率准则计算小波系数的萎缩因子,然后在考虑尺度因素和方向能量因素的基础上对萎缩因子进行修正并将之应用于小波系数萎缩过程中,最后通过逆变换得到降噪和增强的图像.试验结果表明,在损失较小峰值信噪比值的情况下,提出的方法在增强图像细节和边缘、加大图像对比度等方面要优于直接比例萎缩,能够获得较好的视觉效果.给出的小波系数增强思想可以应用于基于其它降噪准则的比例萎缩算法中.
침대소파역비례위축강조방법재거제조성적동시야약화료도상세절화변연적결함,제출료구유증강효과적기우최대후험개솔준칙적소파역자괄응강조산법,병장지응용우홍외도상강조중.해산법재가정도상계수화조성계수선험위고사분포적기출상,이용최대후험개솔준칙계산소파계수적위축인자,연후재고필척도인소화방향능량인소적기출상대위축인자진행수정병장지응용우소파계수위축과정중,최후통과역변환득도강조화증강적도상.시험결과표명,재손실교소봉치신조비치적정황하,제출적방법재증강도상세절화변연、가대도상대비도등방면요우우직접비례위축,능구획득교호적시각효과.급출적소파계수증강사상가이응용우기우기타강조준칙적비례위축산법중.
In order to solve the fault of weakening the detail and edge of image while denoising in wavelet domain,this paper presented an adaptive denoising algorithm with detail enhancing and applied it to infrared image.On the basis of the assumption that the prior distribution of the original image coefficients and the noise coefficients were both Gaussian,this method firstly made use of the rule of Maximum a Posteriori to compute the shrinkable factor for wavelet coefficients,then revised it by taking decomposable level and directional energy into account.Finally,a denoising and enhancing image could be obtained when the wavelet coefficients which were shrunk by the revised shrinkable factor experienced the reverse transform.The experimental results show that the method given by this paper,compared with the direct proportional shrinkage,can enhance image's detail and improve image's contrast and get better visual effect though it has a little loss of Peak Signal Noise Ratio.The idea of coefficients' enhancement in wavelet domain proposed by this paper can apply to other proportional shrinkable algorithms.