ρ-GGD source modeling for wavelet coefficients in image/video coding
Chia-Yang Tsai, Hsueh‐Ming Hang · 2008
ρ-GGD source model is proposed in this paper. The probability distribution of wavelet coefficients has been previously modeled as Laplacian or generalized Gaussian distribution (GGD). The Laplacian model is simple in calculation but not accurate; on the other hand, GGD is accurate but requires a very complicated modeling procedure. In this paper, we introduce a new parameter ρ into the GGD source model, where ρ is the probability of zero-value coefficients. The shape parameter of the GGD model can then be easily estimated from ρ and the standard deviation. Moreover, a piecewise linear approximation method is proposed to further reduce complexity. Our experiments show that the ρ-GGD model has high accuracy and consistent performance for modeling the wavelet coefficient pdfs for both spatial 2-D DWT and interframe wavelet video cases.