Due to complexity constraints, most computer vision (CV) features are not suitable for certain applications such as low-power always-on applications. To address such issues, a contrast-adaptive normalized pixel difference (CA-NPD) is proposed. Unlike conventional NPD techniques, the CA-NPD smooths a metric surface, optimizes contrast discriminability, and enables context sensitive normalization.