Novel Approach for Mixed Pixel Extraction from Remote Sensing Images
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Abstract
In remote sensing imagery presence of mixed pixels while performing the classification process is the biggest. Detecting and classifying the target pixels like minerals and artificial objects from RSI has a huge interest in various applications. In most of the existing techniques the pure pixels (endmembers) can be detected by using seven band values of the capturing satellite. But if those values are not available, then in such situations theses existing algorithms don not able to perform. To solve this problem we proposed a novel technique which used superpixels (based on only RGB values) for preprocessing and classify the given image by using random forest classifier to classify the image into pure and mixed pixels. This proposed method performs better than the existing techniques in terms of accuracy, RMSE and computing time.
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