摘要
为了使去噪后的图像具有更佳的视觉效果,基于新近出现的一种小波域阈值去噪方法——NeighShrink,提出了一种具有细节增强效果的小波域图像去噪方法——增强型邻域收缩方法(enhanced NeighShrink,ENS)。该方法一方面继承了NeighShrink方法的优点,在对小波系数进行阈值处理时,由于考虑了其与邻域系数的相关性,从而大大减少了误判图像细节为噪声的情况,同时,通过改变NeighShrink方法中小波系数收缩因子的计算方法,用该方法去噪后的图像取得了高于NeighShrink方法的峰值信噪比;另一方面,通过引入一个细节增强因子P,使得该方法能够对图像细节进行增强,从而得到了更佳的视觉效果。通过实验证明,该方法能够在去噪和细节增强这两方面优于普通软阈值去噪方法和NeighShrink方法。
Wavelet image denoising is an important method of image denoising. Recently, many different schemes of wavelet image denoising were proposed. Among these, NeighShrink suggested by G. Y. Chen et. al. has been proved very efficient. NeighShrink differs from traditional threshold methods in that it incorporates neighboring coefficients when shrinking wavelet coefficients, and thus avoids killing too much image details. In order to improve the visual quality of the denoised image, a new wavelet image denoising method, namely enhanced NeighShrink（ENS） , is proposed in this paper based on the NeighShrink scheme. By changing the way to calculate the shrinkage factor for the wavelet coefficient, ENS achieves statistically better results than original NeighShrink method in denoising. Moreover, by introducing an extra parameter P in our wavelet scale dependent shrinkage factor calculation scheme, ENS can be used to enhance image details while denoising the image. This feature can be used to improve the visual quality of the image, since the original NeighShrink method, like many other schemes, shrinks all wavelet coefficients, which will incur the loss of the image details to some extent. Experimental results show that ENS can achieve better results in both denoising and enhancing of image details than the traditional soft threshold and NeighShrink methods.
出处
《中国图象图形学报》
CSCD
北大核心
2007年第1期51-55,共5页
Journal of Image and Graphics
基金
上海市科委科研基金项目(012912059)
关键词
小波变换
图像去噪
邻域窗口
图像增强
wavelet transform, image denoising,neighboring window,image enhancement
