In remote sensed images

mixed pixels are always present.Soft classification defines the membership degree of these pixels for different land cover classes.Sub-pixel mapping is a technique designed to use the information contained in these mixed pixels to obtain a sharpened image.Pixels are divided into sub-pixels

representing the land cover class fractions.Evolutionary agent algorithms

combined with the assumption of spatial dependence

assign a location to every sub-pixel through two reactive behaviors which are breeding and diffusion.In the paper

the algorithm is tested on degraded synthetic and real imagery.The obtained accuracy measures are higher compared with conventional hard classifications

so it is proved to be a simple and effective method for sub-pixel mapping.