Skip to Main content Skip to Navigation
Preprints, Working Papers, ...

Sparse representations and dictionary learning: from image fusion to motion estimation

Abstract : The first part of this paper presents some works conducted with Jose Bioucas Dias for fusing high spectral resolution images (such as hyperspectral images) and high spatial resolution images (such as panchromatic or multispectral images) in order to build images with improved spectral and spatial resolutions. These works are related to Bayesian fusion strategies exploiting prior information about the target image to be recovered constructed by dictionary learning. Interestingly, these Bayesian image fusion methods can be adapted with limited changes to motion estimation in pairs or sequences of images. The second part of this paper explains how the work of Jose Bioucas Dias has been a source of inspiration for developing new Bayesian motion estimation methods for ultrasound images.
Document type :
Preprints, Working Papers, ...
Complete list of metadata

https://hal.inria.fr/hal-03130465
Contributor : Nora Ouzir Connect in order to contact the contributor
Submitted on : Wednesday, February 3, 2021 - 3:47:24 PM
Last modification on : Friday, January 21, 2022 - 3:11:22 AM

Identifiers

  • HAL Id : hal-03130465, version 1

Citation

Jean-Yves Tourneret, Adrian Basarab, Nora Leïla Ouzir, Qi Wei. Sparse representations and dictionary learning: from image fusion to motion estimation. 2021. ⟨hal-03130465⟩

Share

Metrics

Les métriques sont temporairement indisponibles