摘要
针对实验图像光照不均、对比度低等特点,提出一种基于非下采样Contourlet变换和PCNN的图像增强算法。首先对原图进行非下采样Contourlet变换,得到高频和低频子带;然后对低频系数进行加权平均,对高频系数采用PCNN进行处理,最后在进行NSCT逆变换,得到增强后的图像。实验结果表明,该方法能很好地展现图像弱边缘细节,进一步提高了峰值信噪比,获得更好的视觉效果。
An image enhancement algorithm is proposed based on Nonsubsampled Contourlet transform and PCNN, to tac- lde the problem that is experimental image has the feature of uneven illumination, low contrast. In this algorithm, we conduct NSCT to the image that to be enhanced, get low and high frequency subband; and use weighted average processing to low- frequency part, and adopt the PCNN to high-frequency part. In the end, make the contrary NSCT in order to achieve image enhancement. The experimental results show that the method can show a good image weak edge detail, to fikrt.her improve the peak signal-to-noise ratio, and obtain better visual effects.
出处
《科教导刊》
2013年第7期193-194,共2页
The Guide Of Science & Education
基金
北方民族大学研究生创新项目(2012XYC030
2011ZYC036)
