Texture classification for multi-spectral images using spatial and spectral Gray Level Differences

Abstract

This paper deals with the development of a new texture analysis method based on both spatial and spectral information for texture classification purposes. The idea of Generalized Gray Level Difference Method (GGLDM) is to extend the concept of spatial Gray Level Difference Method(GLDM) by assuming texture joint information between spectral bands. In addition, new texture features measurement related to (GGLDM) which define the image properties have been also proposed. Extensive experiments have been carried out on many multi-spectral images for use in prostate cancer diagnosis and quantitative results showed the efficiency of this method compared to the Gray Level Difference Method (GLDM). The results indicate a significant improvement in classification accuracy.