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Intelligent identification of background and foreground in video scenes is used for gain compression. This is implemented as a two layer object model in a software-only video compressor with a bit rate range from less than 10 kbps up to to 1.2 Mbps. Quadtree decomposition on an error metric between the input and transmitted images directs the coder towards a foreground layer of active image fragments. A rate buffering system limits the bandwidth by transmitting only the foreground blocks which most improve the image and are above some error threshold. A high fidelity background layer is identified and communicated to the decoder, which can be used to redraw background fragments as foreground objects move across them. Blocks can be coded by various methods, such as fractal transforms or truncated DCTs. This system can be implemented in RISC processors without the need for dedicated hardware. It is suitable for low bit rate applications with slowly varying backgrounds, such as personal video communications over packet networks, or closed circuit TV surveillance using fixed or wireless links.
Nicholls et al. (Tue,) studied this question.