Denoising based on non-local means for ultrasound images with simultaneous multiple noise distributions

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.

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Conference papers
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https://hal.telecom-paristech.fr/hal-02286884
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Submitted on : Friday, September 13, 2019 - 4:18:53 PM
Last modification on : Tuesday, November 5, 2019 - 7:34:02 PM

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  • HAL Id : hal-02286884, version 1

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Denis Salvadeo, Isabelle Bloch, Florence Tupin, Nelson Mascarenhas, Alexandre Levada, et al.. Denoising based on non-local means for ultrasound images with simultaneous multiple noise distributions. IEEE International Conference on Image Processing, Oct 2014, Paris, France. pp.2699-2703. ⟨hal-02286884⟩

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