一种基于小波变换的图像去噪新方法

A New Method Based on Wavelet Transform for Image Denoising

为了更好地进行图像去噪,提出了一种图像去噪的方法。对图像进行小波变换以后,噪声的小波系数在不同尺度上都服从高斯分布但大小不同。由此,对各尺度各方向上的小波系数进行维纳滤波,而保持低频系数不变,先以此来估计原始图像的小波系数;然后进行小波反变换,得到去噪图像。实验结果表明了该方法的有效性。

A method for image denoising is proposed. After performing multi-resolution wavelet decomposition on corrupted image, the wavelet coefficients of noise are Gaussian distribution, and have different variances in different levels. Based on this, wiener filter is applied to the wavelet coefficients on different subbands and orientations, and leave wavelet coefficients in the low frequency domain without change, to estimate the wavelet coefficients of the clean image. Then the inverse wavelet transform is applied to the modified wavelet coefficients, resulting in the denoised image. At the end, experimental results show the validity of the proposed method.