IMAGE DENOISING BASED ON THE DYADIC WAVELET TRANSFORM AND IMPROVED THRESHOLD
Wavelet transform has shown a strong capability to filter out noise that existed in images. The main problem to improve denoising performance lies in the fact that it is difficult to select suitable wavelet transform and related thresholds. In this paper, we completely explore characteristics of dyadic wavelet transform and its possible use to image denoising. An improved threshold method is elaborately designed to establish the self-adjusted layer threshold function and wavelet reconstruction. Theoretical analysis shows that denoising precision can be improved by way of adopting different thresholds according to the different scales of the wavelet coefficients of image and noise. Experiment results demonstrated that our method is obviously superior to that of fixed threshold regarding the effect of image denoising.
image denoising dyadic wavelet transform threshold function signal-noise ratio