POLYNOMIAL-APPROXIMATION AND VECTOR QUANTIZATION - A REGION-BASED INTEGRATION

The paper presents an adaptive scheme for image-data compression. It i s a region-based approach that suitably integrates two different appro aches to image coding, vector quantization (VQ) and polynomial approxi mation (PA). The scheme is adaptive from the point of view of the huma n observer: the perceptually most significant areas are those near edg es or details. In smoothed areas, PA can be used with notable results, but there VQ must be employed to ensure high fidelity. The two techni ques exhibit a complementarity in both advantages and drawbacks. PA is not efficient in compressing high-frequency areas, but yields the bes t results when applied to highly correlated data. VQ is unable to reac h high-compression ratios because of its low adaptability, but is quit e suitable for compressing uncorrelated data. The means to achieve the integration of the two techniques is a control image containing infor mation about edge and texture locations. In the paper, edge encoding a nd restoration are also addressed, which are closely related to the pr oposed hybrid scheme; block prediction is also utilized to further red uce the residual redundancy between VQ blocks. The exploitation of the best features of both approaches results in high compression factors, and in perceivable good quality. In particular, bitrates range from 0 .15 to 0.07 bpp. Main applications of this compression scheme are in t he areas of very-low bitrate image transmission and image archiving.