Discrete cosine transform encoding of two-dimensional processes

The performance of a two-dimensional (2D) block discrete cosine transform (DCT) operating on 2D first-order separable autoregressive Gauss-Markov processes and real-world images is studied. In each case, Lloyd-Max and entropy-constrained quantizers with optimum rate-allocation are employed. These results are compared to the earlier developments for vector predictive quantizers and entropy-constrained 2-D differential pulse code modulation (DPCM). Relative performance improvements that can be obtained for the schemes under consideration, when operating on the same source (either stochastic or select real-world images), are established. The results obtained for real-world images indicate the degree to which the theoretical results can be extended to practical applications