摘要
深入分析VisuShrink阈值和NormalShrink阈值的原理,本文提出了一种改进的自适应阈值图像抑噪算法。该算法根据噪声在不同的小波分解尺度下呈现出不同的特性,估计每层的噪声方差,从而确定适合各个尺度级的自适应最优阈值,并依此对图像进行抑噪。实验结果表明,与传统的均值滤波、中值滤波、VisuShrink阈值法、自适应多阈值法、NormalShrink法、自适应阈值小波去噪法相比较,改进算法所得图像的视觉效果和峰值信噪比均得到改善。
After Donoho＇ s VisuShrink and Lakhwinder Kaur＇ s Normal Shrink are deeply analyzed, an improved adaptive wavelet threshold algorithm on image suppression is proposed. According to the differ- ent characteristics of noise at different wavelet scales, an optimal threshold of each scale is determined by estimation of noise variance. Experimental results show that our algorithm is superior to some traditional spatial filters and new-developed methods based on wavelet both in visual effect and peak signal noise ratio （PSNR）.
出处
《中国体视学与图像分析》
2009年第2期152-155,共4页
Chinese Journal of Stereology and Image Analysis
基金
国家自然科学基金(60803088)
陕西省自然科学基金(2007D07)
中国博士后科学基金(20060401009)
关键词
小波变换
图像抑噪
自适应阈值
wavelet transform
image suppression
adaptive threshold value
