摘要
图像去噪是遥感图像处理的一个重要方面。文中基于非抽取小波变换,提出了一种贝叶斯图像去噪方法。对小波系数采用广义高斯分布建模,根据贝叶斯估计理论,得到贝叶斯收缩阈值,采用软阈值收缩去噪。实验结果表明:该去噪方法能够有效地抑制正交小波变换产生的人为干扰和伪Gibbs现象,与正交小波变换阈值去噪方法相比具有明显的优越性。
Image denoising is an important aspect for remote sensing image processing. A new Bayesian denoising algorithm based on undecimated discrete wavelet transform （UDWT） is presented in this paper. The BayesShrink threshold is derived in a Bayesian framework, and the prior model used on the wavelet coefficients is the generalized Gaussian distribution （GGD）.Image denosing is finished by using Donoho＇ s soft threshoiding. Experiment results show that the new algorithm can reduce the artifacts and the pseudo-Gibbs phenomena from the orthogonal wavelet transform, and has obvious superiority as compared with orthogonal wavelet denoising method.
出处
《通信技术》
2009年第3期223-224,230,共3页
Communications Technology
关键词
图像去噪
非抽取小波变换
贝叶斯估计
image denoising
undecimated discrete wavelet transform
Bayesian estimation.
