Fractal-based dimensionality reduction of hyperspectral images

The spectral reflectance of any pixel in a remote sensing image depends on the characteristics of the particular land cover (LC) present in the Instantaneous Field of View (IFOV) of the sensor. The fractal dimension of the spectral reflectance curve (SRC) of any pixel can thus be visualized as a representation of the characteristics of the LC. Based on this, a fractalbased method for reduction of the dimensionality of Hyperspectral (HS) images has been investigated. The fractal dimension (FD) of SRC has been calculated by adopting a method based on Hausdorff metric that reduces the dimensionality from N HS bands to a single feature incorporating the characteristics associated with each of the bands. Further, it has been established that FD values can be used as a feature to identify anomaly in water cover.