학술논문

Speckle reduction on ultrasound image by variational methods and adaptive Lagrangian multipliers
Document Type
Conference
Source
2004 2nd IEEE International Symposium on Biomedical Imaging: Nano to Macro (IEEE Cat No. 04EX821) Biomedical Imaging: Nano to Macro Biomedical Imaging: Nano to Macro, 2004. IEEE International Symposium on. :547-550 Vol. 1 2004
Subject
Bioengineering
Computing and Processing
Signal Processing and Analysis
Speckle
Ultrasonic imaging
Lagrangian functions
Discrete wavelet transforms
Wavelet coefficients
Noise level
Image analysis
Scattering
Interference
Image restoration
Language
Abstract
Ultrasound images are corrupted by a multiplicative noise, the speckle, which makes high level analysis difficult. Within each resolution cell a number of elementary scatterers reflects the incident wave towards the sensor. The backscattered coherent waves with different phases undergo a constructive or a destructive interference in a random manner. This paper proposes a method of restoration based on variational principles applied to wavelet coefficients. The idea of this process is to avoid the various difficulties caused by wavelet coefficients thresholding, substituting it by a total variation-based technique. The method is based on orthogonal wavelets and uses the conventional separable two-dimensional discrete wavelet transform (DWT) scheme. The coefficients of the different levels are filtered by the total variation algorithm. Nevertheless, in order to comply with ultrasound images statistics, we have adapted the constraints commonly applied to Euler-Lagrange equations. After stating first results on synthetic image, we will validate our model on real images.