EBMBDT: Effective Block Matching Based Denoising Technique using dual tree complex wavelet transform

In processing and investigation of digital image denoising of images is hence very important. In this paper, we propose a Hybrid de-noising technique by using Dual Tree Complex Wavelet Transform (DTCWT) and Block Matching Algorithm (BMA). DTCWT and BMA is a method to identify the noisy pixel information and remove the noise in the image. The noisy image is given as input at first. Then, bring together the comparable image blocks into the load. Afterwards Complex Wavelet Transform (CWT) is applied to each block in the group. The analytic filters are made use of by CWT, i.e. their real and imaginary parts from the Hilbert Transform (HT) pair, defending magnitude-phase representation, shift invariance, and no aliasing. After that, adaptive thresholding is applied to enhance the image in which the denoising result is visually far superior. The proposed method has been compared with our previous de-noising technique with Gaussian and salt-pepper noise. From the results, we can conclude that the proposed de-noising technique have shown better values in the performance analysis.