Image foveation based on vector quantization

Summary form only given. The perceptual resolution of vision is greatly space variant and is highest at the point of fixation and decreases rapidly away from this point. Novel unstructured and structured vector quantization (VQ) schemes are proposed to take advantage of this property of the human visual system (HVS) by providing the best image quality around the fixation point. As a foveation technique, the unstructured VQ does not enjoy progressive transmission in the sense that any request of improvement in the ROI is always replied by complete retransmission of image vectors with a higher resolution VQ scheme. The structured VQ, which is based on a residual vector quantizer (RVQ), yields an embedded progressive bit stream. The main idea for the RVQ foveation is to use more quantization stages for image vectors closer to the fixation point. This method allows the receiver to change its fixation point without any waste of transmitted information and to have multiple fixation points. This quantization strategy enables gradual image resolution change from the ROI to the background.