Hybridization of filter and wrapper approaches for the dimensionality reduction and classification of hyperspectral images
| Autor: | Ahmed Hammouch, Elkebir Sarhrouni, Maria Merzouqi, Chafik Nacir, Asma Elmaizi |
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| Rok vydání: | 2017 |
| Předmět: |
FOS: Computer and information sciences
business.industry Computer science Computer Vision and Pattern Recognition (cs.CV) Dimensionality reduction Computer Science - Computer Vision and Pattern Recognition 0211 other engineering and technologies Hyperspectral imaging Pattern recognition Image processing 02 engineering and technology Mutual information Filter (signal processing) Support vector machine Statistical classification Redundancy (information theory) Artificial intelligence business 021101 geological & geomatics engineering |
| Zdroj: | ATSIP |
| DOI: | 10.1109/atsip.2017.8075549 |
| Popis: | The high dimensionality of hyperspectral images often imposes a heavy computational burden for image processing. Therefore, dimensionality reduction is often an essential step in order to remove the irrelevant, noisy and redundant bands. And consequently, increase the classification accuracy. However, identification of useful bands from hundreds or even thousands of related bands is a nontrivial task. This paper aims at identifying a small set of bands, for improving computational speed and prediction accuracy. Hence, we have proposed a hybrid algorithm through band selection for dimensionality reduction of hyperspectral images. The proposed approach combines mutual information gain (MIG), Minimum Redundancy Maximum Relevance (mRMR) and Error probability of Fano with Support Vector Machine Bands Elimination (SVM-PF). The proposed approach is compared to an effective reproduced filters approach based on mutual information. Experimental results on HSI AVIRIS 92AV3C have shown that the proposed approach outperforms the reproduced filters. Keywords - Hyperspectral images, Classification, band Selection, filter, wrapper, mutual information, information gain. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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