Implementation of Adaptive Wavelet Thresholding and Nonlocal Means for Medical Image Enhancement for Noise Reduction

International Journal of Computer Trends and Technology (IJCTT)          
© 2015 by IJCTT Journal
Volume-24 Number-1
Year of Publication : 2015
Authors : Prerna Mamgain, Sachin Chaudhary
DOI :  10.14445/22312803/IJCTT-V24P105


Prerna Mamgain, Sachin Chaudhary "Implementation of Adaptive Wavelet Thresholding and Nonlocal Means for Medical Image Enhancement for Noise Reduction". International Journal of Computer Trends and Technology (IJCTT) V24(1):23-28, June 2015. ISSN:2231-2803. Published by Seventh Sense Research Group.

Abstract -
Images are most widely used for radiological diagnosis in medical examinations. The presence of artifacts and noise in images causes the difficulty in medical diagnosis. The noises are generally occurred and corrupt an image during its acquisition or transmission. Image denoising is one of the popular methods with an aim of noise reduction to retain images quality. In this paper, Wavelet based noise reduction technique is proposed to improve image quality where thresholding and Non-local means algorithm are applied. The Noisy medical image is decomposed using DWT, where approximation part is filtered using Nonlocal means filter and detail parts are filtered by the thresholding. By using the level dependent, the wavelet coefficients are calculated using optimal linear interpolation shrinkage function. Denoised image is acquired using inverse DWT. The value of the peak signal to noise ratio (PSNR) is used as the measure of image visual quality.

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DWT, PSNR, denoising, thresholding, decomposition.