基于曲波变换和色度模型的彩色图像去噪  

Denoising method for color images based on chrominance model and curvelet transform

作　　者：张云强[1] 张培林[1] 王国德[1] 卓洪波[2] 

机构地区：[1]军械工程学院 [2]75134部队

出　　处：《中国图象图形学报》2012年第12期1472-1477,共6页Journal of Image and Graphics

基　　金：国家自然科学基金项目(50705097);清华大学摩擦学国家重点实验室开放基金项目(SKLTKF09B06)

摘　　要：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 fiher 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 Ganssian noise re- moval in color images.

关 键 词：HSI空间 图像去噪 色度模型 曲波变换 高斯噪声 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]