基于SVM和小波系数的图像去噪算法研究

Research of Image Denoising Based on Support Vector Machine and Wavelet Coefficients

摘要: 结合小波系数的性质和SVM的优点,提出一种基于SVM和小波系数的图像去噪算法,选取特定的支持向量,输入到训练机中进行训练,然后得到最优的分类函数,最后用最优分类函数对含噪图像进行去噪处理.仿真结果表明,该方法具有很好的去噪效果,且能达到较高的峰值信噪比.

Abstract: In this paper,a wavelet-based image denoising using SVM the nature of the wavelet coefficients is proposed.Selecting a specific support vector machine,inputing it into training for training,then get the optimal classification function,and finally with the optimal classification function for noisy image denoising.Simulation results show that the method has a good denoising effect,can achieve higher peak signal to noise ratio.