Insightful Visualization of Remote Sensing Images

Numerous dimensions exist in remote sensing imagery (RSI) dataset, necessitating visualization to display and enable human analysis. In order to visualize, dimension reduction (DR) is performed to decrease the dimensionality to two or three. This letter proposes a novel DR technique called nonlinear local linear embedding (NLLE), where the objective is to obtain an accurate visualization of RSI datasets. NLLE reduces the high dimension of large datasets to a space with low dimensionality, preserving the neighborhood relationship between points in the original space. When compared to other well-known DR techniques, NLLE’s flexible procedure increases the likelihood of achieving effective RSI visualization.