DocumentCode :
248671
Title :
Denoising based on non local means for ultrasound images with simultaneous multiple noise distributions
Author :
Salvadeo, Denis H. P. ; Bloch, Isabelle ; Tupin, Florence ; Mascarenhas, Nelson D. A. ; Levada, Alexandre L. M. ; Deledalle, Charles-Alban ; Dahdouh, Sonia
Author_Institution :
DEMAC, Sao Paulo State Univ., Rio Claro, Brazil
fYear :
2014
fDate :
27-30 Oct. 2014
Firstpage :
2699
Lastpage :
2703
Abstract :
In this paper, an extension of the framework proposed by Deledalle et al. [1] for Non Local Means (NLM) method is proposed. This extension is a general adaptive method to denoise images containing multiple noises. It takes into account a segmentation stage that indicates the noise type of a given pixel in order to select the similarity measure and suitable parameters to perform the denoising task, considering a certain patch on the image. For instance, it has been experimentally observed that fetal 3D ultrasound images are corrupted by different types of noise, depending on the tissue. Finally, the proposed method is applied to denoise these images, showing very good results.
Keywords :
image denoising; image segmentation; image denoising; image segmentation; multiple noise distributions; ultrasound images; Equations; Image segmentation; Mathematical model; Noise; Noise measurement; Noise reduction; Ultrasonic imaging; image denoising; multiple noises; non local means; ultrasound image; ultrasound segmentation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing (ICIP), 2014 IEEE International Conference on
Conference_Location :
Paris
Type :
conf
DOI :
10.1109/ICIP.2014.7025546
Filename :
7025546
Link To Document :
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