Wavelet Based Image DE-Noising with Optimized Thresholding Using HHO Algorithm

This paper presents image de-noising in wavelet domain utilizing optimization algorithm combined with thresholding function. In this study, we utilized the nature inspired metaheuristic optimizer in order to obtain the optimal solutions for the parameters of thresholding function. Despite the TNN based noise reduction, while applying optimization algorithm there is no need to use LMS learning algorithm to find the optimal threshold value. Applying Harris Hawk Optimization (HHO) algorithm which includes threshold function leads to find the optimized thresholded wavelet coefficients. In this research, smooth sigmoid based shrinkage (SSBS) has been utilized to be combined with the HHO algorithm as the proposed method. Then, applying inverse discrete wavelet transform on the optimized wavelet coefficients provides us with the output de-noised image. The results have shown the efficiency of the proposed technique over other alternative methods in the literature.