Adaptive DCT image coding based on a three-component image model

The authors described a three-component image model developed based on psychovisual studies of the human visual system. This image model consists of the primary component which contains the strong edge information of the image, the smooth component which represents the background slow-intensity variations, and the texture component which contains the textures. Using the image model, an adaptive discrete cosine transform (DCT) image coder is developed in order to achieve high subjective performance at low bit rates (⩽0.5 b/pixel). The simulation results show that this adaptive DCT coder performs better than JPEG both objectively (in PSNR) and subjectively, especially at low bit rates