Abstract
Speckle noise removal by means of digital image processors could improve the diagnostic potential of medical ultrasound. This paper addresses the speckle suppression issue within the framework of wavelet analysis. As a first step of our approach, the logarithm of the original image is decomposed into several scales through a multiresolution analysis employing the 2-D wavelet transform. Then, we design a maximum a posteriori (MAP) estimator, which relies on a recently introduced statistical representation for the wavelet coefficients of ultrasound images [1]. We use an alpha-stable model to develop a blind noise-removal processor that performs a non-linear operation on the data. Finally, we compare our technique to current state-of-the-art denoising method applied on actual ultrasound images and we find it more effective, both in terms of speckle reduction and signal detail preservation.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 2553-2556 |
| Number of pages | 4 |
| Journal | Annual Reports of the Research Reactor Institute, Kyoto University |
| Volume | 3 |
| State | Published - Dec 1 2001 |
| Event | 23rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society - Istanbul, Turkey Duration: Oct 25 2001 → Oct 28 2001 |
Keywords
- Alpha-stable distributions
- MAP estimation
- Speckle noise
- Wavelet transform
ASJC Scopus subject areas
- Energy Engineering and Power Technology
- Mechanical Engineering