Due to the sample-and-hold nature of Liquid Crystal Display (LCD) image formation, LCDs suffer from motion picture blur. This is especially evident during scenes containing fast motion due to the inherent sample-and-hold nature of LCD image formation. Using models for the Human Visual System (HVS) we take a signal processing approach to solving this problem by pre-processing the data before it is sent to the display. Whereas previous pre-processing approaches either apply a simple high pass filter or an iterative deconvolution algorithm, this work uses a small collection of efficient linear FIR filters to reduce the amount of perceived motion blur. Specifically, we develop a two-channel non-perfect reconstruction filter bank to reduce the motion dependent low pass effects of the HVS. Perceptual tests indicate that our algorithm reduces the amount of perceived motion blur on LCDs at a lower complexity than the existing deconvolution approach.