This paper addresses the generic issue of texture image analysis using local spectra features that are based on space/spatial-frequency (s/sf) analysis methods. The two-dimensional (2D) Wigner distribution (WD) and its discrete implementation pseudo-Wigner distribution (PWD) are discussed. A set of new local spectral features is derived from a simple decorrelation procedure (principal component analysis-PCA) of the PWD. In order to assess the feasibility of the features for characterizing local texture properties, texture segmentation experiments have been carried out using these features with the help of the fuzzy-c mean clustering algorithm. The segmentation results show that PWD allows us to extract the intrinsic features of texture image regions, and that using the proposed local spectral features yields satisfactory texture segmentation results.