Low bit-rate coding of image sequences using adaptive regions of interest

An adaptive algorithm for extracting foreground objects from background in videophone or videoconference applications is presented in this paper. The algorithm uses a neural network architecture that classifies the video fram es in regions-of-interest (ROI) and non-ROI areas, also being able to autom atically adapt its performance to scene changes, The algorithm is incorpora ted in motion-compensated discrete cosine transform (MC-DCT)-based coding s chemes, allocating more bits to ROI than to non-ROI areas, Simulation resul ts are presented, using the Claire and Trevor sequences, which show reconst ructed images of better quality, as well as signal-to-noise ratio improveme nts of about 1.4 dB, compared to those achieved by standard MC-DCT encoders .