Speckle Noise Reduction in Medical Ultrasound Images
Ultrasound imaging is an incontestable vital tool for diagnosis, it provides in non-invasive manner the internal structure of the body to detect eventually diseases or abnormalities tissues. Unfortunately, the presence of speckle noise in these images affects edges and fine details which limit the contrast resolution and make diagnostic more difficult. In this paper, we propose a denoising approach which combines logarithmic transformation and a non linear diffusion tensor. Since speckle noise is multiplicative and nonwhite process, the logarithmic transformation is a reasonable choice to convert signal-dependent or pure multiplicative noise to an additive one. The key idea from using diffusion tensor is to adapt the flow diffusion towards the local orientation by applying anisotropic diffusion along the coherent structure direction of interesting features in the image. To illustrate the effective performance of our algorithm, we present some experimental results on synthetically and real echographic images.
Keywords: Ultrasound images, Homomorphic transformation, Anisotropic diffusion, Denoising, Structure tensor, Diffusion tensor.
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ABOUT THE AUTHORS
Faouzi Benzarti
Faouzi Benzarti: is an associate professor at the High School of Technology and Science of Tunisia (ESSTT). He received his Engineer’s degree in Electrical Engineering from the Engineering School of Monastir (TUNISIA) in 1987, and his master’s degree in Biomedical Engineering from the Polytechnic School of Montreal CANADA in 1991. He obtained his Ph.D degree from the Engineering School of Tunis (ENIT) in 2006. He is a member of research group in the Signal, Image and Pattern Recognition Laboratory TSRIF. His current researches include: Image Deconvolution, Image Inpainting, Anisotropic diffusion, Image retrieval, 3D Biometry.
Hamid Amiri
Hamid Amiri: is a Professor at the National Engineering School of Tunis (ENIT) Tunisia. He received the Diploma of Electro-technics, Information Technique in 1978 and the PHD degree in1983 at the TU Braunschweig, Germany. He obtained the Doctorates Sciences in 1993. From 2001 to 2009 he was at the Riyadh College of Telecom and Information. Currently. He is now thea head member of research group in the Signal, Image and Pattern Recognition Laboratory. His research is focused on Image Processing, Speech Processing, Document Processing and Natural language processing.
Faouzi Benzarti
Faouzi Benzarti: is an associate professor at the High School of Technology and Science of Tunisia (ESSTT). He received his Engineer’s degree in Electrical Engineering from the Engineering School of Monastir (TUNISIA) in 1987, and his master’s degree in Biomedical Engineering from the Polytechnic School of Montreal CANADA in 1991. He obtained his Ph.D degree from the Engineering School of Tunis (ENIT) in 2006. He is a member of research group in the Signal, Image and Pattern Recognition Laboratory TSRIF. His current researches include: Image Deconvolution, Image Inpainting, Anisotropic diffusion, Image retrieval, 3D Biometry.
Hamid Amiri
Hamid Amiri: is a Professor at the National Engineering School of Tunis (ENIT) Tunisia. He received the Diploma of Electro-technics, Information Technique in 1978 and the PHD degree in1983 at the TU Braunschweig, Germany. He obtained the Doctorates Sciences in 1993. From 2001 to 2009 he was at the Riyadh College of Telecom and Information. Currently. He is now thea head member of research group in the Signal, Image and Pattern Recognition Laboratory. His research is focused on Image Processing, Speech Processing, Document Processing and Natural language processing.
