该文利用经验模态分解技术对图像进行分解,获得表示图像不同频率属性的各个固有模态函数分量,并将代表图像高频信息和次高频信息的固有模态函数嵌入到Perona-Malik模型中。改进后的模型不仅在对高斯噪声降噪时优于原Perona-Malik模型,而且对椒盐噪声也能较好地去除。
In this paper, an image denoising model which embeds intrinsic mode function into Perona-Malik model is proposed. Firstly, the image is decomposed into Intrinsic Mode Functions (IMFs) by using empirical mode decomposition technique; each of IMFs captures the feature information under different scales. Secondly, the first and second IMFs are embedded into Perona-Malik model. Experimental results indicate that this method is more efficient than Perona-Malik model in removing Gaussian noise. Moreover, this method can remove salt and pepper noise.