基于朴素贝叶斯分类的图像消噪

Image Denoising Using Naive Bayesian Classification

图像消噪是图像分割和识别的必要预处理。根据噪声的统计特征和频谱分布规律以及图像特点,人们提出并发展了多种不同的图像消噪方法。基于朴素贝叶斯分类决策的图像消噪效果良好,在图像消噪和细节保留上取得了合理的平衡。

It is necessary for the image denoising to preprocess for its segmentation and recognition. Many methods of the image denoising are proposed based on the statistical features of noise, spectral distribution, and image. The experimental result shows that it is good effective and is reasonable equilibrium between images denoising and preserving details for the image denoising using naive Bayesian classification decision.