Abstract: To better handle the flat tail phenomenon commonly seen in transform coefficients such as DCT coefficients, a system and method having a model dubbed a transparent composite model (TCM) are described. Given a sequence of transform coefficients, a TCM first separates the tail of the sequence from the main body of the sequence. A first distribution such as a uniform, truncated Laplacian, or truncated geometric distribution can be used to model transform coefficients in the flat tail while at least one parametric distribution (e.g. truncated Laplacian, generalized Gaussian (GG), and geometric distributions) can be used to model data in the main body. A plurality of boundary values can be used to bound a plurality of distribution models. The plurality of boundary values and other parameters of the TCM can be estimated via maximum likelihood (ML) estimation or greedy estimation.