In this paper the use of a perceptually-motivated image model in the context of image compression is investigated. The model consists of a so-called primary component which contains the strong edge information of the image, a smooth component which represents the background slow-intensity variations and a texture component which contains the textures. The primary component, which is known to be perceptually important, is encoded separately by encoding the intensity and geometric information of the strong edge brim contours. Two alternatives for coding the smooth and texture components are studied: Entropy-coded adaptive DCT and entropy-coded subband coding. It is shown via extensive simulations that the proposed schemes, which can be thought of as a hybrid of waveform coding and featurebased coding techniques, result in both subjective and objective performance improvements over several other image coding schemes and, in particular, over the JPEG continuous-tone image compression standard. These improvements are especially noticeable at low bit rates. Furthermore, it is shown that a perceptual tuning based on the contrast-sensitivity of the human visual system can be used in the DCT-based scheme, which in conjunction with the 3- component model, leads to additional subjective performance improvements.