This chapter covers the metrics of general feature description, often used for whole images and image regions, including textural, statistical, model-based, and basis space methods. Texture, a key metric, is a well-known topic within image processing, and it is commonly divided into structural and statistical methods. Structural methods look for features such as edges and shapes, while statistical methods are concerned with pixel value relationships and statistical moments. Methods for modeling image texture also exist, primarily useful for image synthesis rather than for description. Basis spaces, such as the Fourier space, are also used for feature description.