A framework for real-time adaptive delivery of web images to resource-constrained devices is presented, bringing together techniques from image analysis, compression, rate-distortion optimization, and user interaction. Two fundamental themes in this work are: (1) a structured and scalable representation, obtained through content- and lower-level image analysis, that allows multiple descriptions of object regions, and (2) resource-optimized content adaptation in real time, facilitated by an algorithm for directly merging LZ77-compressed streams without the need for additional string matching.
Also introduced is a new distortion measure for image approximations based on a feature space distance. Using this measure, a color reduction algorithm is proposed. Simulation studies show that this algorithm can yield better results than previous approaches, both from a visual standpoint and in terms of feature space distortion.