Abstrait

Noise Reduction of Enhanced Images Using Dual Tree Complex Wavelet Transform and Shrinkage Filter

S. Arulmozhi, D.N. Keerthikumar

The project presents that noise reduction of enhanced images using Dual tree complex wavelet transform and Bivariate shrinkage filter.Enhanced image gets affected during contrast enhancement process.So the denoising process will be handled to reduce distortion under Dual tree complex wavelet transform domain. Initially noisy image pixels are decorrelated to obtain coarser and finer components and more noise details are contaminated in high frequency subbands. In order to reduce the spatial distortion during filtering, bivariate shrinkage function used in the DTCWT domain.The effect of noise in the images can be reduced by using either spatial filtering or transform domain filtering. In transform domain wavelet method provide better de-noising while preserving the details of images like edges. In order to increase the quality of the super resolved image, preserving the edges is essential.The guided filter is not directly applicable for sparse inputs like strokes. It also shares a common limitation of other explicit filter,it may have halos near some edges.In order to overcome these disadvantages Dual Tree Complex Wavelet Transform (DTCWT) is used which provide perfect reconstruction over the traditional wavelet transform.Experimental results show that the resultant algorithms produce images with better visual quality and at the same time performance can be improved.Evaluation is carried out in terms of various parameters such as Peak Signal to Noise Ratio, mean Structural Similarity and Coefficient of Correlation.