Hybrid image coding scheme incorporating human visual system characteristics

Abstract

In this paper, a hybrid image coding scheme combining the advantages of both classified vector quantization (CVQ) and discrete cosine transform (DCT) is proposed. An image vector is classified according to its content activity. Vectors of low activity (shade vectors) are coded using CVQ. For vectors of high activity (edge vectors), DCT is used. To enhance the visual quality of the decoded image, the modulation transfer function (MTF) of the human visual system (HVS) model is incorporated into the DCT coding algorithm. Simulation results showed that the proposed approach allowed good subjective image quality to be obtained at relatively low bit rates. The improvement in quality is even more pronounced at low bit rates, if this scheme is compared to those schemes employing CVQ or DCT alone.