Abstract
Noise estimation is a precursor to de-noising techniques to improve the signal and visual quality of medical images. We present a noise estimation algorithm using the local image statistics of the CT images at voxel level. The algorithm calculates the local mean variance distribution and detects the minimised error rates for identifying the tolerance range of voxel to artificial noises. The reliability of the method is experimentally verified using Gaussian noise and Speckle noise on CT scan images.
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James, A.P., Kavitha, A.P. (2014). Mean-Variance Blind Noise Estimation for CT Images. In: Thampi, S., Gelbukh, A., Mukhopadhyay, J. (eds) Advances in Signal Processing and Intelligent Recognition Systems. Advances in Intelligent Systems and Computing, vol 264. Springer, Cham. https://doi.org/10.1007/978-3-319-04960-1_21
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DOI: https://doi.org/10.1007/978-3-319-04960-1_21
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-04959-5
Online ISBN: 978-3-319-04960-1
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