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Bhadauria, H. S.
- Performance Analysis of Denoising Methods on Brain CT Images
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Authors
Affiliations
1 Department of Electrical Engineering, Indian Institute of Technology, Roorkee-247667, IN
2 Department of Computer Sc. & Engineering, G. B. Pant Engineering College, Pauri-Garhwal, OM
1 Department of Electrical Engineering, Indian Institute of Technology, Roorkee-247667, IN
2 Department of Computer Sc. & Engineering, G. B. Pant Engineering College, Pauri-Garhwal, OM
Source
Digital Image Processing, Vol 5, No 3 (2013), Pagination: 145-149Abstract
This paper presents a comparative assessment of various denoising methods on brain CT images. The paper quantitatively compares total of four denoising methods namely wiener filter, median filter, anisotropic diffusion and total variation (TV). The focus of this work is to compare these methods not only for the suppression of noise but also for the preservation of fine details and edges on brain CT images. The experimental results show that the wiener filter shows the best performance in terms of perceptual quality, noise suppression and edge preservation. It yields the higher values of SNR, PSNR, UQI and EKI as compared to other denoising methods. This is an evidence of the maximum noise suppression with significant edges and fine details preservation.Total variation method induces some staircase effect and loss of fine details. Wavelet based method yields better denoising particularly in homogenous regions but does not gives better results in edgy regions and anisotropic diffusion method shows blurring effect and thus edges and fine details are lost.Keywords
Computed Tomography (CT), Total Variation (TV), Anisotropic Diffusion (AD).- Edge Detection of Noisy Abnormal Lung CT Image Based on Combined Wavelet Transform and Canny Operator
Abstract Views :133 |
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