Mixture-Based Superpixel Segmentation and Classification of SAR Images
US$53.15
10000 in stock
SupportDescription
A mixture-based superpixel segmentation method for synthetic aperture radar (SAR) images. The method uses SAR image amplitudes and pixel coordinates as features. The feature vectors are modeled statistically by taking into account the SAR image statistics. We resort to finite mixture models to cluster the pixels into superpixels. After superpixel segmentation, we classify different land covers such as urban, land, and lake using the features extracted from each superpixel.