Subpixel Target Size Estimation for Remotely Sensed Imagery

One of challenges in remote sensing image processing is subpixel detection where the target size is smaller than the ground sampling distance. In this case, targets of interest have their sizes less than the pixel resolution, therefore, embedded in a single pixel. Under such a circumstance, these targets can be only detected spectrally at subpixel level, not spatially as ordinarily conducted by classical image processing techniques. This paper investigates a more challenging issue than subpixel detection, which is subpixel target size estimation. More specifically, when a single pixel-embedded target is detected, we would like to know what is the size of this particular target within the pixel. Our proposed approach is fully constrained linear spectral unmixing (FCLSU), which allows us to estimate the abundance fraction of the target present in the pixel that determines the size of the target. In order to evaluate the proposed FCLSU, two sets of experiments are conducted, computer simulations and real HYDICE data, where computer simulations are used to plant targets to validate our approach and real data are used to demonstrate the utility of the FCLSU in practical applications.