IEEE Trans Image Process. 2014 Dec;23(12):5165-74. doi: 10.1109/TIP.2014.2362058. Epub 2014 Oct 8.
This paper introduces an image denoising procedure based on a 2D scale-mixing complex-valued wavelet transform. Both the minimal (unitary) and redundant (maximum overlap) versions of the transform are used. The covariance structure of white noise in wavelet domain is established. Estimation is performed via empirical Bayesian techniques, including versions that preserve the phase of the complex-valued wavelet coefficients and those that do not. The new procedure exhibits excellent quantitative and visual performance, which is demonstrated by simulation on standard test images.
本文介绍了一种基于二维尺度混合复值小波变换的图像去噪方法。同时使用了最小（酉）和冗余（最大重叠）两种变换形式。建立了小波域白噪声的协方差结构。通过经验贝叶斯技术进行估计，包括保留复值小波系数相位的版本和不保留相位的版本。新方法在标准测试图像上的模拟结果表明，它具有出色的定量和视觉性能。
