自适应收缩函数的Contourlet 变换图像去噪方法

针对传统图像在去噪过程中存在丢失细节且去噪效果不理想的情况，提出一种自 适应收缩函数的Contourlet 变换图像去噪方法。该方法利用Contourlet 变换的基本形式，结合 软阈值和硬阈值收缩函数的优点定义自适应收缩函数，并将其应用于图像去噪。实验结果表明， 所提出的方法能有效消除噪点，图像的峰值信噪比及增强因子等图像质量指标有明显地提高， 去噪后图像的视觉效果良好。

Image Denoising Based on Adaptive Contraction FunctionContourlet Transform

To solve some problems on image denoising, such as losing details and falling into poor effects, a method of image denoising is proposed based on adaptive contraction function Contourlet transform algorithm. According to the basic Contourlet transform form and combing the soft threshold and hard threshold contraction function, the adaptive contraction function is defined. Experimental results show that the proposed method can greatly remove noise, effectively improve peak signal to noise ratio, mean squared error and image enhancement factor of image quality index. After combining the improved threshold function, the image has better visual quality.