In this paper a hierarchical model for early visual processing is presented and its applicability to image processing problems is demonstrated. The model consists of arrays of processing units, or neurons, arranged in layers that are retinotopically connected. The principal feature of this architecture is that neighboring neurons exert mutually inhibitory interactions only. It is shown that the proposed model can generate the center-surround (CS) and the orientation- selective (OS) receptive field profiles observed in the early parts of the mammalian visual system. Our study reveals that the receptive field sensitivity profile depends on the lateral extent of the inhibitory interactions. The OS receptive field requires a larger number of lateral inhibitory interactions than does a CS receptive field. Furthermore, it is found that the lateral extent of inhibition can be reduced by cascading CS layers with OS layers. Finally, the applicability of the model to feature detection and image enhancement is also investigated.