摘要
提出一种基于全变差(TV)模型和小波包变换的图像去噪算法,并给出了针对该模型的一种改进正则化参数选取方法,改善了全变差模型去噪中出现的块效应问题,同时保留了图像中的边缘信息.数值实验表明,用所给算法去噪可得到较高的峰值信噪比和较好的视觉效果.
Authors proposed an effcient image denoising method based on the combination of wavelet packet transform with total variation model and presented how to select the regularization parameter in this model.The combination of wavelet packet transform with total variation model helps to alleviate staircase effect efficiently and preserve sharp discontinuities in images as well.The numerical experimental results show that the new method is effective in removing Gaussian noise and keep the detail of the image well.
出处
《吉林大学学报（理学版）》
CAS
CSCD
北大核心
2014年第1期81-85,共5页
Journal of Jilin University:Science Edition
基金
国家自然科学基金(批准号:10926157)
吉林大学基本科研业务费专项基金(批准号:2012BS043)
关键词
图像处理
图像去噪
全变差模型
小波包变换
image processing
image denoising
total variation model
wavelet packet transform
