Image denoising based on the dyadic wavelet transform

Since subsampling does not take place in image dyadic wavelet transform at each level, image representation in dyadic wavelet domain compared with wavelet series reconstruction is very redundant and part of disturbance of image dyadic wavelet coefficients in transform domain will not lead to serious distortion. Therefore, with the same error decision probability, the better reconstruction can be expected. Based on this idea, this paper extends the existing wavelet-based image denoising approaches to the dyadic wavelet-based image denoising (DWID). Numerical experiments show that DWID can significantly improve the power signal-to-noise ratio.