Hybrid Distributed Correlation Noise Model and Parameter Estimation
In transform domain distributed video coding scheme, we found that there was a certain deviation between Laplacian statistical distribution and the distribution of small and large residual coefficients. To reduce this deviation, this paper proposes a hybrid distribution correlation noise model (HDCNM) based on K-Mediods, which models small coefficients as improved Laplacian distribution while modeling large ones as Cauchy distribution. The parameter estimation algorithm is also given. The experimental results show that the hybrid model proposed in this paper can describe the distribution of residual coefficients between WZ frame and side information accurately, so as to improve the distortion performance of transform domain distributed video coding effectively, and reduce the computational complexity of decoder.