摘要
针对传统小波阈值去噪算法的不足,提出了一种新的自适应阈值去噪算法。该算法引入了一个新的阈值函数,利用GGD模型对小波子带内的系数进行建模,再根据小波子带系数的局部邻域信息进行方差估计,从而得到自适应最优阈值。实验结果表明,该算法在峰值信噪比和主观视觉效果上都比传统小波阈值去噪算法具有明显改善。
To improve the performance of traditional wavelet threshold denoising algorithm, A new adaptive threshold denoising algorithm is proposed. First, a new threshold function is produced ; Second, a model for wavelet coefficients is presented, in which each co- efficient in a sub - band is obeyed to general Gaussian distribution ; Third, in order to obtain the adaptive optimal threshold, the variance is estimated from the local neighborhood information of sub - band wavelet coefficients. Experiment results demonstrate that the proposed algorithm has a better peak signal -to- ratio and subjective vision effect, compared to traditional wavelet threshold denoising algorithm.
出处
《微计算机应用》
2008年第1期15-18,共4页
Microcomputer Applications
关键词
图像去噪
小波变换
阈值函数
image denoising, wavelet transform, threshold function
