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Wavelet-Based Medical Infrared Image Noise Reduction Using Local Model for Signal and Noise Publisher



Kafieh R1 ; Rabbani H1
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Authors Affiliations
  1. 1. Biomedical Engineering Department, Medical Image and Signal Processing Research Center, Isfahan, University of Medical Sciences, Isfahan, Iran

Source: IEEE Workshop on Statistical Signal Processing Proceedings Published:2011


Abstract

This paper presents a new wavelet-based denoising method for medical infrared images. Since the dominant noise in infrared images is signal dependent we use local models for statistical properties of (noise-free) signal and noise. In this base, the noise variance is locally modeled as a function of the image intensity using the parameters of the image acquisition protocol. In the next step, the variance of noise-free image is locally estimated and the local variances of noise-free image and noise are substituted in a wavelet-based maximum a posterior (MAP) estimator for noise removal. Our simulations illustrate that proposed technique outperforms other denoising methods including non-local methods. © 2011 IEEE.
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