A Laplacian-Cauchy Mixture Model for Improved Correlation Noise Modeling in Distributed Video Coding

A novel Laplacian-Cauchy Mixture Distribution (LCMD) model is proposed to characterize the distribution of correlation noise between the original Wyner-Ziv frame and the side information in transform domain distributed video coding schemes. Observing the deviations of traditional Lapalcian modeled distribution on large and small residual coefficients, to reduce the deviations, a LCMD model is proposed by modeling small Discrete Cosine Transform (DCT) coefficients as improved Laplacian distributed while modeling large ones as Cauchy distributed. Two solutions to find parameters of LCMD model are also proposed. Real video experiments demonstrate the improvements of LCMD in terms of both the Rate Distortion (RD) performance and computation complexity.