Translator Disclaimer
29 December 2008 Classification of multispectral images by using Lagrangian support vector machines
Author Affiliations +
Proceedings Volume 7285, International Conference on Earth Observation Data Processing and Analysis (ICEODPA); 72850E (2008) https://doi.org/10.1117/12.815783
Event: International Conference on Earth Observation Data Processing and Analysis, 2008, Wuhan, China
Abstract
Lagragian support vector machine (LSVM) is a linearly convergent Lagrangian, which is obtained by reformulating the quadratic program of a standard linear support vector machine. To investigate the performance of the classifier working on multispectral images with LSVM as optimizer, we devise a new test based on LSVMs for classifying multispectral data in this work. First of all, data are preprocessed. To acquire the optimum bands for image classification, multispectral image is mapped into a two-dimensional feature space to inspect the bands with redundant spectral information. These extracted data acquired through the feature selection is named data group B relative to the original data group A for a purpose of comparison. Then, to classify multiclass problem, binary classification is extended to multiclass classification by pairwise method. Secondly, two groups of data are trained to find models. In this phase, optimal C values are chosen carefully through trials with different values. Then, classifiers based on LSVMs with optimal C values are used to yield optimal separating hyperplane (OSH). Lastly, in prediction phase, the two groups of data are inputted respectively into each classifier for testing. These classifiers include ones with linear kernel and ones with polynomial kernel of degree 2. The results of the experiment reveal that classifiers with LSVMs as an optimizer have excellent performances with both linear kernel and polynomial kernel of degree 2. Bias caused by the differentia of the two groups of data is not obvious.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Hongmei Zhu and Xiaojun Yang "Classification of multispectral images by using Lagrangian support vector machines", Proc. SPIE 7285, International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72850E (29 December 2008); https://doi.org/10.1117/12.815783
PROCEEDINGS
8 PAGES


SHARE
Advertisement
Advertisement
Back to Top