This paper presents a simple and efficient method for estimation of parameters useful for textured image analysis. On the basia of a 2-D Wold-like decomposition of homogenenous random fields, the texture field can be decomposed into a sum of two mutually orthogonal components: a deterministic component and an indeterministic component. The spectral density function (SDF) of the former is a sum of 1-D or 2-D delta functions. The 2-D autocorrelation function (ACF) of the latter is fitted to the assumed anisotropic ACF that has an elliptical contour. The parameters representing the ellipse and those representing the delta functions can be used to detect rotation angles and scaling factors of test textures. Specially, rotation and scaling invariant parameters, which are applicable to the classification of rotated and scaled textured images, can be estimated by combining these parameters. That is, a test texture can be correctly classified even if it is rotated and scaled. Several computer experiments on natural textures show the effectiveness of this method.