Using superpixels to improve the efficiency of Laplacian Eigenmap based methods for target detection in hyperspectral imagery

摘要

LE-based methods have been shown to be effective for target detection in HSI. However, they can be slow due to the costly graph construction and eigenvector computation steps. In this paper, we proposed including a step of pre-segmenting an HSI into superpixels prior to dimensionality reduction. Carrying out experiments on an HIS from the SHARE 2012 data campaign, we show that incorporating superpixels in the BNC target detection method can yield much faster computation times without sacrificing accuracy. When incorporated in SE-based target detection, superpixels do cause a slight decrease in accuracy. Future work involves a more thorough validation on multiple datasets, and testing whether or not the inclusion of superpixels is useful for other target detection algorithms.