A class of vector quantizers with memory that are known as finite state vector quantizers (FSVQs) in the image coding framework is investigated. Two FSVQ designs, namely side match vector quantizers (SMVQs) and overlap match vector quantizers (OMVQs), are introduced. These designs take advantage of the 2-D spatial contiguity of pixel vectors as well as the high spatial correlation of pixels in typical gray-level images. SMVQ and OMVQ try to minimize the granular noise that causes visible pixel block boundaries in ordinary VQ. For 512 by 512 gray-level images, SMVQ and OMVQ can achieve communication quality reproduction at an average of 1/2 b/pixel per image frame, and acceptable quality reproduction. Because block boundaries are less visible, the perceived improvement in quality over ordinary VQ is even greater. Owing to the structure of SMVQ and OMVQ, simple variable length noiseless codes can achieve as much as 60% bit rate reduction over fixed-length noiseless codes. >

Side match and overlap match vector quantizers for images

A speech coder employs vector quantization of LPC parameters, interpolation, and trellis coding for improved speech coding at low bit rates (400 bps). The speech coder has an LPC analysis module for converting input speech to LPC parameters, an LSP conversion module for converting LPC parameters into line spectrum frequencies (LSP) data, and a vector quantization and interpolation (VQ/I) module for encoding the LSP data into vector indexes for transmission by applying LPC spectral amplitude as weighting coefficients to the LSP data. The VQ/I module outputs one vector index for every two LPC frames in order to reduce the transmission bit rate, and the omitted frames are interpolated on the receiving end. A decoder correspondingly decodes incoming indexes to LPC parameters and synthesizes them into output speech. Trellis coders with an adaptive tracking function encode the pitch and gain parameters of the LPC frames. A universal codebook stores codewords according to a plurality of accents. The speech coder automatically identifies a speaker's accent and selects the corresponding vocabulary of codewords in order to more intelligibly encode and decode the speaker's speech.

Low-bit-rate speech coder using LPC data reduction processing

A harmonic speech coding arrangement where vector quantization is used to improve speech quality Parameters are determined at the analyzer (120) of an illustrative coding arrangement to model the magnitude and phase spectra of the input speech A first codebook of vectors is searched for a vector that closely approximates the difference between the true and estimated magnitude spectra A second codebook of vectors is searched for a vector that closely approximates the difference between the true and the estimated phase spectra Indices and scaling factors for the vectors are communicated to the synthesizer (160) such that scaled vectors can be added into the magnitude and phase spectra for use at the synthesizer in generating speech as a sum of sinusoids

Vector quantization in a harmonic speech coding arrangement

A pulse amplitude modulated (PAM) mapper (36) includes a constellation matrix memory (40) string indicating of a plurality of different constellations. The constellations are used individually or together to support a plurality of different modem data rates. The mapper (36) also includes a logic block (60), a constellation controller (65), a PAM code generation block (68), and an output register (75). The logic block receives incoming bits and groups the bits as a function of the desired or agreed upon bit rate as indicated by the constellation controller (65), and provides a plurality of each group of bits to the PAM code generation block (68), and one or more sign bits to the output register (75).

Mapper for high data rate signalling

In a Noise Feedback Coding (NFC) system having a corresponding ZERO-STATE filter structure, the first ZERO-STATE filter structure including multiple filters, a method of producing a ZERO-STATE response error vector. The method includes: (a) transforming the first ZERO-STATE filter structure to a second ZERO-STATE filter structure including only an all-zero filter, the all-zero filter having a filter response substantially equivalent to a filter response of the ZERO-STATE filter structure including multiple filters; and (b) filtering a VQ codevector with the all-zero filter to produce the ZERO-STATE response error vector corresponding to the VQ codevector.

Efficient excitation quantization in noise feedback coding with general noise shaping

A method for resisting the effects of channel noise in the digital transmission of information by means of the technique known as vector quantization, in which the codebook for binary index code assignment is generated by picking a vector quantized codeword with high probability and low perceptually-related distance from a required group of nearest neighbors, assigning that codeword and those neighbors binary index codes differing only in one bit, repeating the steps just outlined for assigned binary index codes to residual codewords until the lasts assignments must be made arbitrarily. Applications include transmission of speech by coded LPC parameters and transmission of image intensity or chrominance blocks for visual images. Such systems also make possible and are attractive for memory-efficient storage of such signals.

Jayant Nuggehally Sampeth

Papers

Resisting the effects of channel noise in digital transmission of information