Airplane Localization in Satellite Images by using Visual Attention

Date

2013-04-26

Author

Ozyer, Gulsah Tumuklu
Yarman Vural, Fatoş Tunay

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

29
views

0
downloads

Automatic target detection from the satellite images is an important tool for various applications including mapping, city planning and defense industry. In this paper, we propose a new two-stage method to identify the airplane regions in the airport images by using visual attention. In the first stage, the interesting patches in the image is aimed to extract from the high resolution images. For that purpose, Itti-Koch visual attention model which is inspired from human vision system is used. In the second stage, the important regions containing airplane in the images are extracted from the patches obtained in the first stage. In that stage, Itti-Koch model is applied to emphasis airplane regions in image patches by utilizing an airplane query image. The experimental results show that the proposed approach is successful to localize the airplane regions from the high resolution satellite images.

Subject Keywords

Remote sensing, Object localization, Visual attention

URI

https://hdl.handle.net/11511/55993

Collections

Department of Computer Engineering, Conference / Seminar

Suggestions

OpenMETU
Core

URBAN BUILDING DETECTION FROM OPTICAL AND INSAR FEATURES EXPLOITING CONTEXT Wegner, J. D.; Ok, Ahmet; Thiele, A.; Rottensteiner, F.; Soergel, U. (2010-09-03) We investigate the potential of combined features of aerial images and high-resolution interferometric SAR (InSAR) data for building detection in urban areas. It is shown that completeness and correctness may be increased if we integrate both InSAR double-bounce lines and 3D lines of stereo data in addition to building hints of a single optical orthophoto. In order to exploit context information, which is crucial for object detection in urban areas, we use a Conditional Random Field approach. It proves to b...
Road extraction from satellite images by self supervised classification and perceptual grouping Şahin, Eda; Ulusoy, İlkay; Department of Electrical and Electronics Engineering (2013) Road network extraction from high resolution satellite imagery is the most frequently utilized technique for updating and correcting geographic information system (GIS) databases, registering multi-temporal images for change detection and automatically aligning spatial datasets. This advance method is widely employed due to the improvements in satellite technology such as development of new sensors for high resolution imagery. To avoid the cost of the human interaction, various automatic and semi-automatic ...
Analysis of near-field ultra-wideband radar imaging algorithms Arabacı, Ahmet; Koç, Seyit Sencer; Department of Electrical and Electronics Engineering (2017) Recently, near-field ultra-wideband radar imaging algorithms have an important place in short range imaging applications by providing high resolution in both range and cross-range. In this study, the near-field ultra-wideband radar imaging algorithms in the literature such as Holographic Image Reconstruction Algorithm, Range Migration Algorithm, MIMO Based Range Migration Algorithm and MIMO Based Kirchhoff Migration Algorithm have been implemented using MATLAB. The algorithms are applied to modeled transmit...
Automatic multi-scale-segmentation of high spatial resolution satellite images using watersheds Şahin, Kerem; Ulusoy, İlkay; Department of Electrical and Electronics Engineering (2013) Useful information extraction from satellite images for the use of other higher level applications such as road network extraction and update, city planning etc. is a very important and active research area. It is seen that pixel-based techniques becomes insufficient for this task with increasing spatial resolution of satellite imaging sensors day by day. Therefore, the use of object-based techniques becomes indispensable and the segmentation method selection is very crucial for object-based techniques. In ...
Building Detection in satellite images by textural features and Adaboost CETIN, MELIH; Halıcı, Uğur (2010-08-24) A method based on textural features and Adaboost for detecting buildings in satellite images is proposed. Several local textural features including mean and standard deviation of image intensity and gradient, Zernike moments, Circular-Mellin features, Haralick features, Fourier Power Spectrum, Wavelets, Gabor Filters, and a set features extracted from HSV color space are extracted. Adaboost learning algorithm is employed for both classification and determining the beneficial feature subset, due to its featu...

Citation Formats

G. T. Ozyer and F. T. Yarman Vural, “Airplane Localization in Satellite Images by using Visual Attention,” 2013, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/55993.