Contourlet变换在图像去噪及融合算法中的应用研究

Research on Application of Contour let Transform in Image De-noising and Fusion Algorithm

在处理高维图像信号时,Contourlet变换比小波变换拥有更好的逼近精度、方向性以及系数表达能力,因此将Contourlet变换应用到图像处理领域已经成为研究热点.总结了Contourlet变换的尺度内和尺度之间的依赖性,提出了基于Contourlet变换的图像去噪算法和图像融合算法,其算法能够较为有效地保留原图像的边缘细节,拥有较好的视觉效果.

Compared with wavelet transform, the contour let transform has better approximation accuracy, orientation and coefficient expression ability in dealing with the high dimensional im- age signal. Therefore, the application of contour let transform to the field of image processing has become a research hotspot. In this study, the dependence between the scale and the scale of contour let transform was summarized. The image de-noising algorithm and image fusion al- gorithm based on contour let transform were proposed, The algorithm can effectively preserve the edge details of the original image and has a better visual effect.