光学技术, 2007, 33 (6): 0906, 网络出版: 2010-06-03
小波域空间自适应图像消噪算法
Adaptive image denoising by exploiting wavelet intra-scale dependency
摘要
基于小波阈值的图像消噪方法是简单而又有效的,对小波系数进行空间自适应的研究可使阈值能自适应于图像的统计特性,可进一步提高消噪性能。分析了现有的自适应建模方法在消噪性能和计算消耗上的不足。在假定小波系数为具有未知分布参数的广义高斯分布随机变量的基础上提出了一种基于方差的上下文局部建模方法,用于估计每个系数所对应的参数。该方法能很好地反映小波系数的局部统计特性。实验证明其消噪效果要好于其它空间自适应建模方法。
Abstract
The method of wavelet thresholding for image denoising has been researched extensively due to its effectiveness and simplicity. Spatially adaptivity can improve the wavelet thresholding performance because it makes threshold value adaptive to the spatially changing statistics of images. After analyzing the defects of current methods,a new spatially adaptive coefficient model is proposed. Each wavelet coefficient is modeled as a random variable of a generalized Gaussian distribution with an unknown parameter,and the modeling is used to estimate the parameter for each coefficient. The method provides a good indication of local variability. Experiments show that higher peak-signal-to-noise ratio and better visual effect can be obtained as compared to other methods.
陈莹, 纪志成, 韩崇昭. 小波域空间自适应图像消噪算法[J]. 光学技术, 2007, 33(6): 0906. CHEN Ying, JI Zhi-cheng, HAN Chong-zhao. Adaptive image denoising by exploiting wavelet intra-scale dependency[J]. Optical Technique, 2007, 33(6): 0906.