基于二阶导数算子与小波变换的图像去噪

二阶导数算子噪声定位的图像去噪法对椒盐噪声有很强的去噪能力，但对高斯噪声去噪效果较差，基于小波变换的图像去噪法能有效去除高斯噪声，但几乎不能去除椒盐噪声。针对上述问题，采用二阶导数算子降噪与小波变换去噪相结合的方法对图像去噪，利用2种方法进行优势互补，能较好地去除椒盐、高斯噪声和椒盐-高斯混合噪声，降低选择阈值的难度，有利于提高图像去噪精度。实验结果表明，该算法是有效可行的。

Image De-noising Based on Second Derivative Operator and Wavelet Transform

An image de-noising method based on second derivative operator to noise location can de-noising impulse noise effectively, but it is not very good to remove Gaussian noise. An image de-noising method based on wavelet transform has the ability to remove Gaussian noise while it hardly de-noises impulse noise. An image de-noising method based on second derivative operator and wavelet transform has some advantages. It has better effect on removing impulse noise, Gaussian noise and impulse-Gaussian mixed noise and it decreases the difficulty of threshold selection, which is good to improve the accuracy of image de-noising. Experimental result shows that this method is effective and feasible.