Abstract: An improved VQ system for compressing a digital signal produces a compressed signal by dividing the signal to be compressed into a series of signal segments. Each signal segment comprises a plurality of signal values. The improved VQ system uses first and second tables of vector values having different degrees of signal correlation, referred to as a class-1 table and a class-2 table respectively. For a selected signal segment, the VQ system determines a vector Xbar1 representing a difference between the signal values in the selected segment and an average of a selected group of signal values in a preceding segment. For the same signal segment, the method and apparatus determines another vector Xbar2 representing a difference between the signal values in the selected signal segment and an average of a selected group of signal values in the selected signal segment. The vectors Xbar1 and Xbar2 measure different levels of correlation between the signal values of the selected signal segment.

Abstract: An improved VQ system for compressing a digital signal produces a compressed signal by dividing the signal to be compressed into a series of signal segments. Each signal segment comprises a plurality of signal values. The improved VQ system uses first and second tables of vector values having different degrees of signal correlation, referred to as a class-1 table and a class-2 table respectively. For a selected signal segment, the VQ system determines a vector Xbar1 representing a difference between the signal values in the selected segment and an average of a selected group of signal values in a preceding segment. For the same signal segment, the method and apparatus determines another vector Xbar2 representing a difference between the signal values in the selected signal segment and an average of a selected group of signal values in the selected signal segment. The vectors Xbar1 and Xbar2 measure different levels of correlation between the signal values of the selected signal segment.

Abstract: An adaptive vector quantization scheme suitable for packet video adapts to the varying characteristics of the actual images sequence being compressed. A large code book is divided into two sections, having higher and lower priority, representing common characteristics and specific characteristics of images. Each new image to be coded is first compared to the common characteristics section of the code book. If a match of acceptable quality is not found, then it is compared to the specific characteristics section. The best match of the two sections is utilized. Entries in the two sections are reorganized and/or exchanged as a function of the usage of the code vectors therein. The rate and extent of adaptation is dictated by the update interval and the desired level of quality, respectively, without requiring any transmission of the vectors themselves or the side information.

Abstract: A vector quantization based image compression technique which exploits inter-block correlation and layered addressing structure to form variable block sizes. Without introducing any quality degradation, when compared to the traditional vector quantization algorithms, the invention described herein significantly increases the compression and reduces the bit rate. The concept of inter-block correlation is utilized to form variable size blocks, which are then coded using a hierarchical coding model. The method is based on starting off from a small basic block which is allowed to grow to a maximum of a preset block size as long as certain conditions are met. The basic idea of growing the block is based on the renormalization group theory in physics. The algorithm utilizes only one pixel code book for the basic block size and several address code books for the layer block sizes to encode an image. S/N ratio in excess of 30 dB at bit rates lower than 0.2 bpp are easily obtained.