摘要: 二阶导数算子噪声定位的图像去噪法对椒盐噪声有很强的去噪能力,但对高斯噪声去噪效果较差,基于小波变换的图像去噪法能有效去除高斯噪声,但几乎不能去除椒盐噪声。针对上述问题,采用二阶导数算子降噪与小波变换去噪相结合的方法对图像去噪,利用2种方法进行优势互补,能较好地去除椒盐、高斯噪声和椒盐-高斯混合噪声,降低选择阈值的难度,有利于提高图像去噪精度。实验结果表明,该算法是有效可行的。
关键词:
二阶导数算子,
椒盐噪声,
高斯噪声,
小波变换,
图像去噪
Abstract: An image de-noising method based on second derivative operator to noise location can de-noising impulse noise effectively, but it is not very good to remove Gaussian noise. An image de-noising method based on wavelet transform has the ability to remove Gaussian noise while it hardly de-noises impulse noise. An image de-noising method based on second derivative operator and wavelet transform has some advantages. It has better effect on removing impulse noise, Gaussian noise and impulse-Gaussian mixed noise and it decreases the difficulty of threshold selection, which is good to improve the accuracy of image de-noising. Experimental result shows that this method is effective and feasible.
Key words:
second derivative operator,
impulse noise,
Gaussian noise,
wavelet transform,
image de-noising
中图分类号:
王绪四, 杨恢先, 谢鹏鹤, 满莎, 彭友. 基于二阶导数算子与小波变换的图像去噪[J]. 计算机工程, 2011, 37(12): 187-189.
WANG Xu-Si, YANG Hui-Xian, XIE Feng-He, MAN Sha, BANG You. Image De-noising Based on Second Derivative Operator and Wavelet Transform[J]. Computer Engineering, 2011, 37(12): 187-189.