Image enhancement of ultrasound images using multifarious denoising filters and GA
Prabhpreet Kaur, Gurvinder Singh, Parminder Kaur · 2016
Medical images are often of low contrast and noisy (lack of clarity) due to the circumstances they are being captured. De-noising of ultrasound images is a difficult task as compare to other medical images because of noise, blurring of edges and artifacts. The Bayesian shrinkage method has been selected for thresholding based on its sub-band dependency property. The spatial domain based de-noising filtering techniques, using soft thresholding method are compared with the proposed method using Genetic Algorithm (GA). A proposed technique includes GA and results are compared with existing spatial domain based de-noising filtering techniques. The proposed algorithm provides enhanced visual clarity for diagnosing the medical images. The proposed method based on GA assesses the better performance on the basis of the quantitative metric like Peak Signal-to-Noise Ratio (PSNR) and Fitness value. The overall simulated result shows that proposed technique outperforms the prevailing de-noising filtering methods in terms of edge preservation and visuality.