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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 the Spatial and Spectral Gray Level Dependence Method (SSGLDM) is to extend the concept of spatial gray level dependence method by assuming texture joint information between spectral bands. In addition, new texture features measurement related to (SSGLDM) 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 Co-occurrence Matrix (GLCM). The results indicate a significant improvement in classification accuracy.