基于提升小波的数字图像混合噪声抑制算法
Mixed Noise Suppression Algorithm of Digital Image Based on Lifting Wavelet
何佑明 1刘睿 2刘金地3
作者信息
- 1. 安徽文达信息工程学院通识教育学院,合肥 231201
- 2. 安徽公安教育研究院警务技能训练部,合肥 230031
- 3. 安徽公安职业学院警体部,合肥 230031
- 折叠
摘要
针对混合噪声特点不一致,抑制难度较大的问题,为提升噪声抑制效果,提高图像清晰度,提出一种基于提升小波的数字图像混合噪声抑制算法.通过概率神经网络将数字图像噪声划分为脉冲噪声和高斯噪声,采用中值滤波方法去除数字图像中的脉冲噪声,运用提升小波方法去除数字图像中的高斯噪声,实现混合噪声的抑制.实验结果表明,所提算法获得的图像清晰度和信噪比更高,且去噪后数字图像的ENOB(Effective Number Of Bits)值明显提升,说明该算法的混合噪声抑制效果更佳.
Abstract
Unlike single noise,mixed noise has inconsistent characteristics and is difficult to suppress.In order to improve the noise suppression effect and image clarity,a digital image mixed noise suppression algorithm based on lifting wavelet is proposed.By using probabilistic neural networks,digital image noise is divided into pulse noise and Gaussian noise.The median filtering method is used to remove pulse noise from the digital image,and the lifting wavelet method is used to remove Gaussian noise from the digital image,achieving mixed noise suppression.The experimental results show that the proposed algorithm achieves higher image clarity and signal-to-noise ratio,and significantly improves the ENOB(Effective Number Of Bits)value of the digital image after denoising,indicating that the hybrid noise suppression effect of the algorithm is better.
关键词
数字图像/中值滤波/提升小波/脉冲噪声/高斯噪声Key words
digital image/median filtering/lifting wavelet/impulse noise/gaussian noise引用本文复制引用
基金项目
安徽省教育厅拔尖人才培育基金资助项目(gxbjZD2021091)
出版年
2024
国家科技期刊平台
NSTL
万方数据