摘要
提出了一种基于双局部阈值的小波收缩的图像去噪算法。该算法利用小波系数的幅值、空间特性以及对噪声图像的分割,得到两个局部阈值:幅度阈值和空间阈值。利用这两个局部阈值(每个区域阈值不同)对小波系数做相应的"收缩"处理和重构,从而得到一个优质的去噪图像。该算法计算简单速度快,去噪效果明显,优于其他一些去噪算法。
This paper presents a wavelet shrinkage algorithm for image denoising based on two-local threshold.This algorithm presents two-local threshold based on the wavelet eoefticients＇magnitude,spatial regularity,and the segment of the denoised image. Shrinking and reconstructing the wavelet coefficients using the two-local threshold,and we can get a high quality image.The algorithm has sortie advantages such as low eomplexity,fast speed computation,high quality image denoising.The performance of the method is an improvement upon sortie other methods in the literature.
出处
《计算机工程与应用》
CSCD
北大核心
2007年第33期63-65,71,共4页
Computer Engineering and Applications
关键词
图像去噪
小波收缩
双局部阈值
二维离散平稳小波变换
image denoising
wavelet shrinkage
two-local threshold
2-D discrete stationary wavelet transform
