Multilayer perceptrons applied to entropy-constrained image coding

To obtain low-complexity solutions for distributed block coding at the focal plane of a camera, we use an entropy-constrained vector quantizer (ECVQ) design algorithm to find a block encoder N that minimizes a rate-distortion Lagrangian cost J over all possible block encoders, and then apply a set of operations to constrain the structure of N to that of a multilayer perceptron (MLP) while keeping J small. The MLP is successful in emulating the ECVQ, with less than 0.2 dB quality loss.