چکیده (انگلیسی):

The image data is normally corrupted by additive noise during acquisition. This reduces the accuracy and
reliability of any automatic analysis. For this reason, denoising methods are often applied to restore the
original image. In proposed method a wavelet shrinkage algorithm based on fuzzy logic and the DT-DWT
scheme is used. In particular, intra-scale dependency within wavelet coefficients is modeled using a fuzzy
feature. This model differentiates the important coefficients and the coefficients belong to image
discontinuity and noisy coefficients. This fuzzy model is used to enhance the wavelet coefficients'
information in the shrinkage step which uses the fuzzy membership function to shrink wavelet coefficients
based on the fuzzy feature. The effectiveness of image denoising depends upon the estimation of noise
variance of noisy image, the noise variance is estimated using smoothing spline Estimation. This study
examine image denoising algorithm in the dual-tree discrete wavelet transform, which is the new
shiftable and modified version of discrete wavelet transform. Simulation result shows our approach
achieves a substantial improvement in both PSNR and Visual quality.