A Step Towards Learning Contraction Kernels for Irregular Image Pyramid

Darshan Batavia, Rocio Gonzalez-Diaz, Walter Kropatsch

2022

Abstract

A structure preserving irregular image pyramid can be computed by applying basic graph operations (contraction and removal of edges) on the 4-adjacent neighbourhood graph of an image. In this paper, we derive an objective function that classifies the edges as contractible or removable for building an irregular graph pyramid. The objective function is based on the cost of the edges in the contraction kernel (sub-graph selected for contraction) together with the size of the contraction kernel. Based on the objective function, we also provide an algorithm that decomposes a 2D image into monotonically connected regions of the image surface, called slope regions. We proved that the proposed algorithm results in a graph-based irregular image pyramid that preserves the structure and the topology of the critical points (the local maxima, the local minima, and the saddles). Later we introduce the concept of the dictionary for the connected components of the contraction kernel, consisting of sub-graphs that can be combined together to form a set of contraction kernels. A favorable contraction kernel can be selected that best satisfies the objective function. Lastly, we show the experimental verification for the claims related to the objective function and the cost of the contraction kernel. The outcome of this paper can be envisioned as a step towards learning the contraction kernel for the construction of an irregular image pyramid.

Paper Citation

in Harvard Style

Batavia D., Gonzalez-Diaz R. and Kropatsch W. (2022). A Step Towards Learning Contraction Kernels for Irregular Image Pyramid. In Proceedings of the 11th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-549-4, pages 60-70. DOI: 10.5220/0010840900003122

in Bibtex Style

@conference{icpram22,
author={Darshan Batavia and Rocio Gonzalez-Diaz and Walter Kropatsch},
title={A Step Towards Learning Contraction Kernels for Irregular Image Pyramid},
booktitle={Proceedings of the 11th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2022},
pages={60-70},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010840900003122},
isbn={978-989-758-549-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 11th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - A Step Towards Learning Contraction Kernels for Irregular Image Pyramid
SN - 978-989-758-549-4
AU - Batavia D.
AU - Gonzalez-Diaz R.
AU - Kropatsch W.
PY - 2022
SP - 60
EP - 70
DO - 10.5220/0010840900003122