Soft-then-hard sub-pixel mapping with multiple shifted images

The soft-then-hard sub-pixel mapping (STHSPM) algorithm is a type of sub-pixel mapping (SPM) algorithm that first estimates the soft class values for sub-pixels at the target fine spatial resolution and then predicts the hard class labels for sub-pixels. In this article, four fast STHSPM algorithms (i.e. bilinear, bicubic, kriging, and radial basis function interpolation) were enhanced by using multiple shifted images (MSIs). The proportion images of the MSIs were first downscaled to the desired fine spatial resolution and then the multiple downscaled images were integrated for each class, followed by the class allocation process. Three remote-sensing images were used to test the proposed methods, and the results showed that MSIs can help to increase the SPM accuracy of the four STHSPM algorithms. The approach to incorporating MSIs into the STHSPM algorithms is non-iterative and fast.