Texture analysis of multi-spectral prostate tissue using Generalised Grey Level Difference Method
by R. Khelifi; M. Adel; S. Bourennane
International Journal of Signal and Imaging Systems Engineering (IJSISE), Vol. 5, No. 2, 2012

Abstract: In this paper, we propose a new approach of multi-spectral texture classification based on both spatial and spectral information. We do this by extending the concept of spatial Grey Level Difference Method (GLDM) and assuming texture joint information between spectral bands. In this manner, we can characterise multi-spectral texture by statistics of absolute difference distributions of pairs of spectral vectors and define new texture features by computing various statistics from such distributions in given relative positions. 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 with the GLDM. The results indicate a significant improvement in terms of global accuracy rate.

Online publication date: Wed, 31-Dec-2014

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