基于尺度间和尺度内相关性的平稳小波红外图像去噪

提出了一种基于尺度间和尺度内相关性的平稳小波变换红外图像去噪方法.首先对红外图像进行离散平稳小波变换,分别对各个分解层的高频子带,利用不同尺度小波系数形成的系数向量,通过线性最小均方误差估计小波系数,获得各个高频子带的估计系数,再利用小波系数尺度内的邻域相关性对小波系数进行修正,然后通过小波反变换得到去噪图像.仿真结果表明,考虑尺度间和尺度内相关性的平稳小波红外图像去噪算法能有效地去除红外图像噪声,在信噪比和视觉质量上要优于单纯考虑尺度间相关性的去噪方法.

Infrared Image Denoising Based on Stationary Wavelet Transform Using Inter-scale and Intra-scale Dependencies

A methods using stationary wavelet transform with inter-scale and intra-scale dependencies for infrared image denoising is proposed.Firstly,infrared image is decomposited using stationary wavelet transform.For the high frequency component of image decomposition,the wavelet coefficient vectors are formed with the different scales.Then the minimum mean square error estimation is applyed to estimated coefficient.The wavelet coefficients are revised using the correlations between coefficients at the same scale.The denoised image is obtained through inverse wavalet transform.The experimental results show the infrared image can be denoised better than the method neglecting the correlations between intra-scales and have a well SNR as well as the visual quality.