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In this case, supervised image classification techniques play a central role.
Image classification was undertaken using both unsupervised and supervised image classification techniques.
Prior to use of this technique, both unsupervised and supervised image classifications were tried.
Then, images were classified at pixel level using supervised image classification with maximum likelihood classifier algorithm.
The accuracy of a supervised image classification is a function of the training data used in its generation.
Then, supervised image classification was done for the image and four classes were identified and mapped; see Fig. 4.
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The watershed transform is a method for non-supervised image segmentation.
The analysis has been realized using multitemporal Landsat TM images through Supervised classification, image processing, vectorialization and GIS tools.
Land cover classes were mapped through the process of a supervised digital image classification (Thomas et al. 1987).
To acquire images of moving solution objects with maximum contrast, the system light source was set at 2.7 V with the camera (AxioCam MRm) at the minimum exposure of 1 ms. Additional detail of the supervised automated image processing can be found in the Supporting Information.
For further reduced computing complexity and feature dimension, this paper introduces a supervised mechanism for image retrieval when a training image set is available.
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