Texture is one of the most important features used in the analysis and interpretation of images. One of the important and primary issues in texture analysis is classification of images based on texture content. A precise classification results in a good analysis. In this book, novel approaches for classification & analysis of rotationally invariant textures were presented. The proposed methods eliminate counting the unnecessary features that do not contribute to increase the quality of the available information hence reduce the dimensionality of a feature set for preserving the most relevant features and the computational cost. These methods help in extracting desired features for a rotationally invariant textures and precise classification. The study should help in further research in developing the algorithms in wavelet domain. One can extend pattern based schemes on the proposed algorithms for image retrieval, texture classification, analysis and synthesis. These empirical studies help researchers and professionals in the field of image processing and stimulate further research.