Most of the snapshot HDR (High Dynamic Range) image sensors have a non-linear, programmable, response curve that requires multiple register settings. The complexity of the settings is such that most algorithms reduce the number of parameters to only two or three and calculate a smooth response curve that approaches a log response. The information available in the final image depends on the compression rate of the response curve and the quantization step of the device. In this early stage proposal, we make use of scene information and discrete information transfer to calculate the response curve shape that maximizes the information in the final image. The image may look different to a human but contains more useful information for machine vision processing. One important field of use of such sensors with programmable dynamic range is automotive on-board machine vision and more specifically autonomous vehicles.