Image representation and processing through multiscale local jet features
Year: 2010
Type: article
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. Key words: feature space, image representation, local jet, scale space, nearest neighbour search, non local means, optical flow, background subtraction, visual salience, multidimensional mode 1
Author: Antoine Manzanera
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2740497168