Aircraft Type Recognition in Remote Sensing Images using Mean Interval Kernel

Jaya Sharma, Rajeshreddy Datla, Rajeshreddy Datla, Yenduri Sravani, Vishnu Chalavadi, Krishna C.

2022

Abstract

Structural characteristics representation and their fine variations are crucial for the recognition of different types of aircrafts in remote sensing images. Aircraft type classification across different sensor remote sensing images by spectral and spatial resolutions of objects in an image involves variable length spatial pattern identification. In our proposed approach, we explore dynamic kernels to deal with variable length spatial patterns of aircrafts in remote sensing images. A Gaussian mixture model (GMM), namely, structure model (SM) is trained over aircraft scenes to implicitly learn the local structures using the spatial scale-invariant feature transform (SIFT) features. The statistics of SM are used to design dynamic kernel, namely, mean interval kernel (MIK) to deal with the spatial changes globally in the identical scene and preserve the similarities in local spatial structures. The efficacy of the proposed method is demonstrated on the multi-type aircraft remote sensing images (MTARSI) benchmark dataset (20 distinct kinds of aircraft) using MIK. Also, we compare the performance of the proposed approach with other dynamic kernels, such as supervector kernel (SVK) and intermediate matching kernel (IMK).

Paper Citation

in Harvard Style

Sharma J., Datla R., Sravani Y., Chalavadi V. and C. K. (2022). Aircraft Type Recognition in Remote Sensing Images using Mean Interval Kernel. In Proceedings of the 2nd International Conference on Image Processing and Vision Engineering - Volume 1: IMPROVE, ISBN 978-989-758-563-0, pages 166-173. DOI: 10.5220/0011062600003209

in Bibtex Style

@conference{improve22,
author={Jaya Sharma and Rajeshreddy Datla and Yenduri Sravani and Vishnu Chalavadi and Krishna C.},
title={Aircraft Type Recognition in Remote Sensing Images using Mean Interval Kernel},
booktitle={Proceedings of the 2nd International Conference on Image Processing and Vision Engineering - Volume 1: IMPROVE,},
year={2022},
pages={166-173},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011062600003209},
isbn={978-989-758-563-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 2nd International Conference on Image Processing and Vision Engineering - Volume 1: IMPROVE,
TI - Aircraft Type Recognition in Remote Sensing Images using Mean Interval Kernel
SN - 978-989-758-563-0
AU - Sharma J.
AU - Datla R.
AU - Sravani Y.
AU - Chalavadi V.
AU - C. K.
PY - 2022
SP - 166
EP - 173
DO - 10.5220/0011062600003209