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Adaptive transform via quantum signal processing: application to signal and image denoising

Raphaël Smith 1 Adrian Basarab 2, 3 Bertrand Georgeot 4 Denis Kouamé 2 
1 IRIT-TCI - Traitement et Compréhension d’Images
IRIT - Institut de recherche en informatique de Toulouse
2 IRIT-MINDS - CoMputational imagINg anD viSion
IRIT - Institut de recherche en informatique de Toulouse
4 Information et Chaos Quantiques (LPT)
LPT - Laboratoire de Physique Théorique
Abstract : The main scope of this paper is to show how tools from quantum mechanics, in particular the Schroedinger equation, can be used to construct an adaptive transform suitable for signal and image processing applications. The proposed dictionary is obtained by considering the signal or image as a discrete potential in Schroedinger equation, further used to construct the Hamiltonien operator. In order to illustrate its practical interest in signal and image processing, we provide denoising results in the case of signal-dependent noise, which is the noise type the most adapted to the proposed approach.
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https://hal.archives-ouvertes.fr/hal-02379093
Contributor : Bertrand Georgeot Connect in order to contact the contributor
Submitted on : Monday, November 25, 2019 - 3:11:00 PM
Last modification on : Friday, August 5, 2022 - 2:56:21 PM

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Raphaël Smith, Adrian Basarab, Bertrand Georgeot, Denis Kouamé. Adaptive transform via quantum signal processing: application to signal and image denoising. IEEE International Conference on Image Processing (ICIP 2018), Oct 2018, Athènes, Greece. ⟨10.1109/ICIP.2018.8451044⟩. ⟨hal-02379093⟩

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