Polynomial approximation and vector quantization: a region-based integration

The paper presents an adaptive scheme for image-data compression. It is a region-based approach that suitably integrates two different approaches to image coding, vector quantization (VQ) and polynomial approximation (PA). The scheme is adaptive from the point of view of the human observer: the perceptually most significant areas are those near edges or details. In smoothed areas, PA can be used with notable results, but there VQ must be employed to ensure high fidelity. The two techniques exhibit a complementarity in both advantages and drawbacks. PA is not efficient in compressing high-frequency areas, but yields the best results when applied to highly correlated data. VQ is unable to reach high-compression ratios because of its low adaptability, but is quite suitable for compressing uncorrelated data. The means to achieve the integration of the two techniques is a control image containing information about edge and texture locations. In the paper, edge encoding and restoration are also addressed, which are closely related to the proposed hybrid scheme; block prediction is also utilized to further reduce 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, bit rates range from 0.15 to 0.07 bpp. Main applications of this compression scheme are in the areas of very-low bit rate image transmission and image archiving.<>