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Image representation and processing through multiscale local jet features

Abstract : We propose a unified framework for representing and processing images using a feature space related to local similarity. We choose the multiscale and versatile local jet feature space to represent the visual data. This feature space may be reduced by vector quantisation and/or be represented by data structures enabling efficient nearest neighbours search (e.g. kd-trees). We show the interest of the local jet feature space processing through three fundamental low level tasks: noise reduction, motion estimation and background modelling/subtraction. We also show the potential of our system in terms of visual representation for higher level (e.g. object modelling and recognition) tasks.
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https://hal.archives-ouvertes.fr/hal-01130881
Contributor : Antoine Manzanera <>
Submitted on : Thursday, March 12, 2015 - 2:52:22 PM
Last modification on : Wednesday, July 3, 2019 - 10:48:05 AM
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  • HAL Id : hal-01130881, version 1

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Antoine Manzanera. Image representation and processing through multiscale local jet features. [Research Report] ENSTA ParisTech. 2010. ⟨hal-01130881⟩

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