Abstract: A method codes a hierarchical subband system of coefficients of a wavelet transform that is representative of an image. One step of this method includes receiving the coefficients of a wavelet transform. A second step includes selecting a first plurality of thresholds ranges. A third step includes comparing the coefficients of a tree structure of coefficients against the plurality of threshold ranges during a first single traversal of the tree structure. A fourth step includes coding the coefficients of the tree structure with symbols based on whether the coefficients are or are not within at least one of the plurality of threshold ranges. A method may include defining a set of symbols for coding a hierarchical subband system of coefficients of a wavelet transform that is representative of an image.

Abstract: A system and method for compressing related data sets of a sequence are disclosed. The process compares domain blocks from a current frame buffer to range blocks in a previous frame buffer or vector quantization ("VQ") tables to generate affine map codes. The affine map codes are preferably encoded by an entropy encoder before being transmitted to a remote site for decompression. The cost for the encoded affine map codes are computed and used to determine whether affine map codes for representing smaller blocks should be included in the affine map codes which represent the domain blocks into which the original frame was segmented. The methods are preferably implemented on a commercially available discrete cosine transform ("DCT") processor having a process controller and a data comparator. The results of the affine map code generating process on the DCT processor achieves a more consistent bit rate and image quality than methods operating the DCT processor to generate DCT codes.

Abstract: A method and apparatus are described for-encoding a three-dimensional array of data representing a physical entity, such as an image (or sequence of frames), by means of its local symmetries. This encoding yields both compression and a resolution-independent description which allows reconstruction of the image to an arbitrary scale. Spatial zooming and interframe interpolation can be achieved without significant loss of information.

Abstract: Digital image data is automatically processed by dividing stored image data into domain blocks and range blocks. The range blocks are subjected to processes such as a shrinking process to obtain mapped range blocks. The range blocks or domain blocks may also be processed by processes such as affine transforms. Then, for each domain block, the mapped range block which is most similar to the domain block is determined, and the address of that range block and the processes the blocks were subjected to are combined as an identifier which is appended to a list of identifiers for other domain blocks. The list of identifiers for all domain blocks is called a fractal transform and constitutes a compressed representation of the input image. To decompress the fractal transform and recover the input image, an arbitrary input image is formed into range blocks and the range blocks processed in a manner specified by the identifiers to form a representation of the original input image.