Unsupervised spectral pattern recognition for multispectral images by means of a genetic programming approach

An innovative approach to spectral pattern recognition for multispectral images based on genetic programming is introduced. The problem is faced in terms of unsupervised pixel classification. The system is tested on a multispectral image with 31 spectral bands and 256-256 pixels. A good quality clustered output image is obtained.