摘要
针对传统阈值函数在图像去噪中存在的缺点和阈值选取的不确定性,为进一步研究小波去噪处理算法,提出了一种新的改进阈值函数的去噪算法,分别对Circuit、Eight、Road 3幅图像采用传统的硬阈值、软阈值、半软阈值方法和文中方法进行Matlab仿真实验。对比分析,文中方法既获得了较好的视觉效果和更高的峰值信噪比,又克服了软阈值信号失真和硬阈值信号不连续、振荡等缺点,且能够在消噪和保留原有信号的弱特征之间获得较好的平衡,明显地改进了传统硬、软阈值函数去噪算法存在的诸多不足,在实际应用中更为有效。
Aimed at the disadvantages of traditional threshold function in image de-noising and the uncer- tainty of the threshold selection, a new improved threshold function algorithm in image de-noising is pro- posed so as to further research on wavelet de-noising algorithm. Matlab simulation of Circuit, Eight, and Road images are performed respectively by adopting the traditional hard threshold, the soft threshold, and the semi-soft threshold method combined with this paper method. Through contrast and analysis, this method is good in visual effects and high in Peak Signal to Noise Ratio （PSNR）. And at the same time, the signal distortion is solved in the soft threshold method, and the signal discontinuity and oscillation shortcomings in the hard threshold method are overcome as well. Moreover, the method can strike a good balance between noise elimination, and can also retain the weak features of the original signal and significantly address many problems in the traditional hard and soft threshold function de-noising algorithms. This method is good in effectiveness in practical applications.
出处
《空军工程大学学报（自然科学版）》
CSCD
北大核心
2016年第1期72-76,共5页
Journal of Air Force Engineering University(Natural Science Edition)
基金
中国科学院寒区旱区环境与工程研究所青年人才成长基金(51Y451291)
关键词
小波变换
改进阈值函数
图像去噪
峰值信噪比
wavelet transformation
improved threshold function
image de-noising
PSNR
