摘要
研究图像优化问题。针对目前常用的空域或频域图像存在各种噪声干扰降低了图像的清晰度,为了在降低图像噪声,保护图像细节和边缘信息,提出一种形态滤波的小波融合图像增强算法MWF。首先分别采用巴特沃斯低通滤波和形态学高帽处理对含噪图像进行滤波,得到两幅过滤的图像,再将这两幅图像分别进行离散小波变换,然后利用变换结果在小波域内依据融合规则进行融合,最后对融合结果进行反变换得到清晰的图像。得到的图像是通过空域滤波和频域增强方法的结合,综合了两种方法各自的优点,仿真结果表明,MWF算法对混合噪声干扰有较好的抑制作用,并实现了图像增强的效果,为图像优化提供了依据。
To cope with the shortcomings in de-noising methods in space domain and frequency domain, a new image fusion algorithm named MWF was proposed based on wavelet transform and gray mathematical morphology. To acquire high quality images, on the basis of lowpass filter, the gray mathematical morphology has been adopted in space domain as well as wavelet transform in wavelet domain. Then two clearer images have been transformed to wavelet coeficients and fusioned by different rule to the coefficients of low frequency and high frequency. Finally, the clear image can be obtained by wavelet inverse transform. This algorithm takes good advantage of lowpass filter and wavelet transform. Simulation experiments show that the MWF algorithm has good effect and the fused image is obviously clear than other images.
出处
《计算机仿真》
CSCD
北大核心
2012年第1期264-268,共5页
Computer Simulation
基金
贵州省科学技术基金(黔科合J字[2009]2112号)
贵州省科技计划(黔科合GY字[2010]3056)
贵阳市科学技术计划项目([2010]筑工合同字第1-57号)
关键词
灰值形态学
小波变换
融合
增强
Gray mathematical morphology
Wavelet transform
Image fusion
hnage enhancement
