摘要
针对图像去噪展开研究,结合均值滤波技术和小波分析技术,提出了使用高斯平滑滤波与小波局部阈值处理相结合的方法。首先对图像进行高斯平滑滤波,然后选取适当的小波阈值对小波系数进行处理、重构得到新的图像,并将去噪图像的峰值信噪比作为性能指标,仿真实验结果表明文中所用的方法去噪效果更佳,图像有着更好的视觉效果。
A method of image denoising technology based on the Gaussian filter and wavelet transformation is proposed. The wavelet threshold denoising is one of the major methods of denoising in the wavelet domain. Firstly, noised image was processed by Gaussian filter and was decomposed by wavelet transformation. Secondly, an appropriate threshold value and decomposed layer were selected. Finally, the image was reconstructed to the first layer and the reconstructed image was reconstructed to the second layer. Simulation results showed that the method not only could remove noise effectively, but also could get higher PSNR value and better visual effect compared with other methods.
出处
《咸阳师范学院学报》
2011年第6期47-49,共3页
Journal of Xianyang Normal University
基金
陕西省科技厅科研基金项目(SJ08ZT14-8
2009JM8021)
咸阳师范学院科研基金项目(08XSYK339)
关键词
均值滤波
高斯滤波
小波分析
图像去噪
mean filter
Gaussian filter
wavelet analysis
image denoising
