Sensitivity analysis of multilayer perceptrons applied to focal-plane image compression

The authors previously considered the application of multilayer perceptrons (MLPs) to block coding at the sensor level of modern imaging systems, and have proposed analogue encoders with transistor-count complexity that is low enough to suit focal-plane implementation. In the paper, they extend the on-sensor block coding MLP study, to include a statistical analysis of the MLP sensitivity to implementation errors occuring in standard CMOS fabrication processes. Employing simple offset models, a comparison is made of the MLP with other block encoders based on full-search entropy-constrained vector quantisation (ECVQ) of the data, and it is verified that the MLPs are less sensitive over a wide range of rate-distortion compression points. By introducing a realistic linear model that takes into account sensitivity and the complexity performances for both systems, the authors verify that, for MLPs, the sensitivity becomes less dependent on the complexity as the expected quality loss is allowed to increase. Without setting a limit on the expected quality loss, the MLPs are consistently better than the ECVQs, both in terms of sensitivity and complexity for a precision equivalent to 6 bits