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.>

A novel approach to video coding at very low bit rates is presented, which differs significantly from most of previous approaches, as it uses a spline-like interpolation scheme in a spatiotemporal domain. This operator is applied to a non-uniform 3D grid (built on sets of consecutive frames) so as to allocate the information adaptively. The proposed method allows a full exploitation of intra/inter-frame correlations and a good objective and visual quality of the reconstructed sequences.>

A new strategy for video coding at very low bit rates is proposed in the paper, where an image sequence is encoded in a two-source way. The main difference from state-of-the-art approaches lies in the use of a 3D spatio-temporal interpolation, based on a non-uniform grid (frames are processed in overlapped blocks), in order to allocate the information in an adaptive way. Experimental results show a good fidelity of the decoded sequences, without blocking effect.>

The authors discuss with the development of a coding system able to reach high compressions of picture data, without notable distortion, by integrating vector quantization and polynomial approximation. The whole process is driven by the latter, while the former is used in textured areas only. The polynomial approximation module is described in depth, together with its integration with the other module. Results obtained on standard images are presented and discussed.>