Denoising based on non local means for ultrasound images with simultaneous multiple noise distributions
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Data
2014-01-28
Autores
Salvadeo, Denis H. P. [UNESP]
Bloch, Isabelle
Tupin, Florence
Mascarenhas, Nelson D. A.
Levada, Alexandre L. M.
Deledalle, Charles-Alban
Dahdouh, Sonia
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Resumo
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.
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image denoising, multiple noises, non local means, ultrasound image, ultrasound segmentation
Como citar
2014 IEEE International Conference on Image Processing, ICIP 2014, p. 2699-2703.