摘要
基于变换的图像压缩方法应用较为广泛,小波在表示图像的边缘或纹理时,会产生大量的能量较大的系数。采用多尺度几何分析对图像进行稀疏展开,使变换具有强的非线性逼近能力。图像经过非下采样Contourlet变换转换成一种多尺度的、多方向和多分辨的表示形式再进行统计分析。利用图像系数相关性,不仅降低图像的维数,使弱的边缘细节能从噪声中被筛选出来,而且达到压缩去噪的目的。实验结果表明,采用该方法去噪后的图像处理效果很好,适用于高分辨率图像去噪。
The image compression method based on transform is widely applied, and when the wavelet is used to indicate the edge or texture of the image, it will produce a large number of coefficients with large energy. The image can be stretched sparsely by means of Multi-scale Geometric Analysis, so that the transform can have stronger nonlinear approximation ability. With undecimated Contourlet transform, images can be transformed into the muhidirectional, polydirectional and multiresolu- tion representation and then be statistically analyzed. With the aid of the correlation of image coefficients, not only the dimension of the image can be reduced so that the weak edge details can be screened out from the noise, but also the purpose of de-noising through compression can be achieved. The Experimental results show that the processing effect of image de-nosing by this method is very good and it is applicable to the de-nosing of high resolution images.
出处
《四川理工学院学报（自然科学版）》
CAS
2014年第4期52-55,共4页
Journal of Sichuan University of Science & Engineering(Natural Science Edition)
基金
国家自然科学基金项目(61171158)
绵阳职业技术学院优秀教学团队资金资助项目(81382013002)
