A Comparative study of various approaches used for the classification of Hyperspectral Satellite Imagery
نویسنده
چکیده
Hyperspectral image classification plays a vital role in today’s era. Identifying the suitable classifier and dimensionality reduction method is a chronic task for the Hyperspectral Image Classification on par with high accuracy and reliability. Image classification using multiple classifier system has been said to be evolving method for improving the accuracy and the reliability. The problems that were faced for identifying the right classifiers and their impact on the computational time and accuracy were reviewed through several papers. Although the multiple classifier system outperforms the support vector machine in all aspects and also it has its own problem of choosing the exact classifier during classification. A Hybrid intelligent system based on the multiple classifier system has been proposed in order to solve the problems that persist in diversity of classifiers and also to determine the number of classifiers that can be used in, related to the image pixel in the classification of Hyperspectral Image.
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