Abstract
This paper presents a GA(Genetic algorithms)-based band selection procedure for producing the color composite image using hyperspectral data (e.g., hyperion data). The more number of hyperspectral bands, the more difficult efficient and effective processing for producing color composite images. In producing color composite images, one of the requirements is to maximize the amount of information in the images (i.e., image entropy). Through GA operations, the increasing of entropy (i.e., fitness value) was confirmed, which corroborates the GA operations can be applied for band selection in producing color composite images. Toward the end of the run, three bands in case of maximizing image entropy are selected, and to produce color composite image, those are assigned to red, blue, and green plane, respectively. Compared with general color composite images (i.e., natural, false, true and ultraviolet color), we conclude that the produced composite image with maximum entropy are useful for image interpretation in terms of the amount of information as well as the image features.
