摘要
为克服传统滤波法在去除高斯噪声时存在的不足,研究了一种基于平移不变小波变换的图像高斯噪声滤波算法,分析了小波分解函数、阈值系数及平移间距对滤波结果的影响。仿真试验表明,文中算法能够在去除噪声的同时较好的保持图像边缘,同时,峰值信噪比也较均值滤波法、小波软阈值和硬阈值等方法有所提高,是一种有效的高斯噪声图像滤波算法。
To de-noise Gaussian noise of images,an image filtering algorithm based on translation invariance wavelet transformation was proposed to overcome shortcomings of classical image filtering algorithms.The influence of wavelet decomposition function,threshold coefficients and translation space on filtering result was also discussed.The simulation results indicate that the proposed algorithm can de-noise and retain the edge of image effectively;Meanwhile,the PSNR was also improved than that of mean filtering and wavelet soft/hard threshold filtering algorithms.It′s an effective Gaussain noise image filtering algorithm.
出处
《弹箭与制导学报》
CSCD
北大核心
2012年第6期140-142,共3页
Journal of Projectiles,Rockets,Missiles and Guidance
基金
国家自然科学基金(61101191)
陕西省自然科学基金(2011JQ8016)
西北工业大学基础研究基金(GBKY1008)
西北工业大学"翱翔之星人才计划"资助
关键词
图像滤波
高斯噪声
平移不变小波变换
阈值收缩
峰值信噪比
image filtering
Gaussian noise
translation invariance wavelet transform
threshold shrinkage
PSNR
