Abstract:

As a promising technique to enhance the spatial resolution of remote sensing imagery, sub-pixel mapping is processed based on the spatial dependence theory with the assumption that the land cover is spatially dependent both within pixels and between them. The spatial attraction is used as a tool to describe the dependence. First, the spatial attractions between pixels, subpixel/pixel spatial attraction model (SPSAM), are described by the modified SPSAM (MSPSAM) that estimates the attractions according to the distribution of sub-pixels within neighboring pixels. Then a mixed spatial attraction model (MSAM) for sub-pixel mapping is proposed that integrates the spatial attractions both within pixels and between them. According to the expression of the MSAM maximumising the spatial attraction, the genetic algorithm is employed to search the optimum solution and generate the sub-pixel mapping results. Experiments show that compared with SPSAM, MSPSAM and pixel swapping algorithm modified by initialization from SPSAM (MPS), MSAM can provide higher accuracy and more rational sub-pixel mapping results.