This study presents an automatic, human perception based chroma-keying algorithm that extracts the objects of interest (i.e. foreground) from monochromatic background. Given an image to be chroma keyed, the global colour distribution and the local texture property are analysed in CIECAM02 colour appearance model. After the analysis, input image is automatically segmented into three parts: foreground, background, and uncertain regions. Afterwards, the background colour is propagated from known background to uncertain region by using interpolation functions; and the foreground colour is estimated based on global colour distribution and a linear cost criteria. The quantitative and perceptual comparisons on the matting results show that the proposed method can reliably remove the background region, correctly restore the intrinsic foreground colour, and accurately keep the fine details. In addition, the authors implement the proposed method on a heterogeneous parallel computing architecture which efficiently distributes the workload among different processors. The simulation results show that the foreground objects can be accurately extracted from high-definition and/or ultra-high-definition videos in real time.