The exchange of visual information in heterogeneous networks requires image compression algorithms that provide high quality images at several spatial resolutions and bit rates. Scalable coding provides images at several resolutions and bit rates, while perceptual coding incorporates human visual system characteristics. This paper presents an image compression algorithm that provides both scalable and perceptual coding to produce an embedded stream suitable for transmission over packet networks. Scalable and perceptual coding are combined through intraband coding of perceptually significant image regions. Images are segmented into
smooth, edge, and detailed regions, and these regions are then independently intraband coded and included in the stream in decreasing order of visual importance with respect to both region type and scale. Visual importance is based on the results of two psychophysical studies analyzing sensitivity to noise in different image regions and their roles in recognition. Locally adaptive quantization, based on study results, is also included in the compression algorithm. The resulting embedded stream provides spatial scalability and region-selective coding and performs well in the presence of packet loss.