Performance Analysis of the Bio-inspired Algorithm with Adaptive Recursive Denoising
A. Ramya, T. Ganesh Kumar, D. Murugan · 2018
This work presents the novel approach based on spatial adaptive filter is presented for image denoising. A new model of noise removal filter is designed with the recursive and adaptive filter and its filter coefficient is led into the Bacterial Foraging Optimization (BFO) algorithm. This cascading process is yields an optimum performance by improving the Peak Signal to Noise Ratio (PSNR) and minimizes the Mean Absolute Error (MAE). The BFO algorithm is a basis of nature-inspired species like bacteria, swarm and bees. This model of denoising filter is experimented on the few standard benchmark images and its performances are evaluated in terms of PNSR and MAE. The denoising filter developed with optimization algorithm gives the better performance and it also gives the consistent result on experimental standard images.