Adaptive DCT coding of images using entropy-constrained trellis coded quantization

An adaptive DCT (discrete cosine transform)-based image coding scheme is developed in which a combination of a perceptually motivated image model, entropy-constrained trellis coded quantization (ECTCQ), and perceptual error weighting is used to obtain good subjective performance at low bit rates. The model is used to decompose the image into strong edge, slow-intensity variations and texture components. The perceptually important strong edges are encoded essentially losslessly. The remaining components are encoded using an adaptive DCT in which the transform coefficients are quantized by ECTCQ. The contrast sensitivity of the human visual system is used for perceptual weighting of the transform coefficients. Objective and subjective results suggest noticeable improvement over JPEG (Joint Photographic Experts Group).<>