A Comparison of the Application of Five Nonlinear Filters to Remove Speckle Noise in Ultrasound Hip Images of Children
Keywords:
Medical image processing, image noise removal, wavelet filter, Perona-Malik filter, Bayesian estimation filter, ultrasound image processing.Abstract
In this study, a comparison was made among the performances of five nonlinear image denoising filters: two types of wavelet filter, two types of and Perona-Malik filter and Bayesian estimation filter. These filters were applied on ultrasound images taken for hip area of children as an initial pre-image process to assess the hip dislocation in children. The results indicated that the Perona-Malik filters performed better than the two wavelet filters based on mean squared error, signal-to-noise ratio and the similarity scale. However, the Bayesian Estimation filter gave the best performance compared to other filters. The only measure that showed variance between Wavelet filters was the homogeneity scale, which is known for its ability to assess noise removal performance separately from improved contrast.
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