Open Access Open Access  Restricted Access Subscription or Fee Access

Ensemble PHOG and SIFT Features Extraction Techniques to Classify High Resolution Satellite Images

S Bharathi, P. Deepa Shenoy, K.R. Venugopal, L M Patnaik


The task of indentifying similar objects within the querying image remains challenging. It is due to viewpoint and lighting changes, deformation and partial occlusions that may exist across different examples. In this framework we focus on combination methods that ensemble multiple descriptors at multiple spatial resolution levels. Ensemble PHOG (Pyramid histogram orientation and gradient) and SIFT (Scale invariant feature transformation) descriptors are used for the feature extraction to achieve the good classification accuracy. Within a region local feature was captured by the distribution over edge orientation, and spatial layout by tiling the image into regions at multiple resolutions. The SIFT features are extracted for each PHOG block. These features are trained using SOM network. Later SVM and Neural network classifiers are used for classification. Results demonstrating the effectiveness of the proposed technique are provided using confusion matrix, transition matrix and other accuracy measures. Area of different land cover regions are calculated, which can be used for land use changes.


PHOG, SIFT, Classification, Satellite Image

Full Text:



Jin Wang, Ping Liuy, Mary F.H.She, Abbas Kouzani, Saeid Nahavandiz “Human Action Recognition Based on Pyramid Histogram of Oriented Gradients”, 978-1-4577-0653-0/11, IEEE 2011.

Navneet Dalal and Bill Triggs, “Histograms of Oriented Gradients for Human Detection”, International Conference on Computer Vision & Pattern Recognition (CVPR '05) France, pp 886—893, 2005.

Dong Wang, Huchuan Lu, Yen-Wei Chen,” Object Tracking By Multi Cues Spatial Pyramid Matching”, Proceedings of 2010 IEEE 17th International Conference on Image Processing, Hong Kong, September 26-29, pp 3957-3960,2010.

He Zhang and Zijun Sha, “Product Classification based on SVM and PHOG Descriptor”, International Journal of Computer Science and Network Security (IJCSNS), VOL.13 No.9, September 2013.

Anna Bosch,Andrew Zisserman,Xavier Munoz, “Representing shape with a spatial pyramid kernel”, CIVR, Amsterdam, The Netherlands, July 9–11, 2007.

Yang Bai, Lihua Guo, Lianwen Jin, Qinghua Huang, “A Novel Feature Extraction Method Using Pyramid Histogram Of Orientation Gradients For Smile Recognition”, ICIP, 978-1-4244-5654-3, China 2009.

Jurgen Bernard, Tatiana von Landesberger, Sebastian Bremm and Tobias Schreck , “Multi-Scale Visual Quality Assessment for Cluster Analysis with Self-Organizing Maps”, International Conference on Visualization and data analysis, California, United States, 4 - 25 January 2011.

Melody Y. Kiang, “Extending the Kohonen self-organizing map networks for clustering analysis”, International Journal of Computational Statistics & Data Analysis, Vol 38, pp 161–180, 2001.

Pavel Stefanoviˇc, Olga Kurasova, “Visual analysis of self-organizing maps”, International Journal of Nonlinear Analysis: Modeling and Control, Vol. 16, No. 4, pp 488–504, 2011.

Fernando Jorge Pires, Victor Lobo, Fernando Bação, “Insights on the interpretation of SOM and U-Matrices with an example clustering based in oceanographic data”, 10th AGILE International Conference on Geographic Information Science, Aalborg University, Denmark.2007.

Ferdinando Giacco, Christian Thiel, Luca Pugliese, Silvia Scarpetta, and Maria Marinaro, “Uncertainty Analysis for the Classification of Multispectral Satellite Images Using SVMs and SOMs”, IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, VOL. 48, NO. 10, OCTOBER 2010.

Xuejun Liu, Zhenfeng Shao, Jun Liu, “Ontology-based image retrieval with SIFT features”, First International Conference on Pervasive Computing, Signal Processing and Applications, 978-0-7695-4180-8, 2010 IEEE.

Chao Tao, Yihua Tan, Huajie Cai, and Jinwen Tian, “Airport Detection From Large IKONOS Images Using Clustered SIFT Keypoints and Region Information”, Ieee Geosciences And Remote Sensing Letters, Vol. 8, No. 1, January 2011.

Bhagawat Rimal, “Application Of Remote Sensing And Gis, Land Use/Land Cover Change In Kathmandu Metropolitan City, Nepal”, Journal of Theoretical and Applied Information Technology,pp 124-131,2011.

C. Cortes and V. Vapnik, “Support vector networks,” Journal of Machine learning,vol. 20(3), pp. 273-297, 1995.


  • There are currently no refbacks.

Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.