Image De-noising Based on Nature Inspired Optimization Algorithm

Noise suppression from the images corrupted by any kind of unwanted signal is a major and challenging issue in the era of image enhancement and computer vision. The purpose of this study is to present a simple and effective iterative multistep image de-noising system based on discrete wavelet transform (DWT) using whale optimization algorithm(WOA). Also presents an algorithm and comparative analysis between discrete wavelet transform and the proposed adaptive wavelet transform (AWT) using whale optimization algorithm. The proposed scheme is tested on images and performance is measured by the various quality indices Peak Signal to Noise Ratio (PSNR), Structural Content (SC), Maximum Difference (MD), Mean Square Error (MSE), Normalized Cross-Correlation (NCC), Average Difference (AD) and Normalized Absolute Error (NAE). Simulation results show that the proposed method is very much successful in removing more noise and the performance of this algorithm is better than basic DWT algorithm.