针对彩色图像中高斯噪声难以去除的问题,提出了一种基于色度模型的色度中值滤波与曲波变换域Bayes多阈值滤波相结合的彩色图像去噪方法。该方法首先将RGB图像转换为HSI图像,通过在色度平面搜索色度中值分别消除H和S分量中的噪声,然后采用循环平移的曲波变换域Bayes多阈值对I分量噪声进行消除,最后通过HSI反变换得到去噪后的彩色图像。对比实验结果表明,本文方法对彩色图像高斯噪声去除,在获得较高峰值信噪比的同时,能较好保留彩色图像的色度、亮度和图像纹理细节信息,避免了"伪影"现象的产生。

Gaussian noise in color images is difficult to remove. We propose a denoising method by combining chrominance median filter based on chrominance model and Bayes multi-threshold filter in the curvelet transform domain. The method converts RGB images to HSI images first. The noise in the H and S components is filtered by searching chrominance median in the chrominance plane. Then, the noise in the I component is removed by using Bayes multi-threshold filter in the cycle spinning curvelet domain. Finally, the denoised color images are produced through the HSI inverse transformation. The contrast experiment results indicate that while achieving higher PSNR, the proposed method can better preserve the color images’ chrominance, intensity as well as texture information, while avoiding yielding artifact effect for Gaussian noise removal in color images.