Adaptive Vector Quantization Scheme Research Articles

A self-organizing adaptive vector quantization technique

This paper describes a new adaptive vector quantization scheme suitable for encoding monochrome and color images. In the proposed technique, a large codebook, consisting of two sections, called higher and lower priority sections, respectively, and representing common and specific characteristics of images, is designed. During encoding the entries in the two sections are reorganized and exchanged as a function of frequency of codevector usage at given intervals. The rate and the extent of adaptation are dictated by the update interval and the desired level of quality, respectively. Adaptation is achieved without requiring any transmission of the vectors themselves. The codebook is expected to adaptively self-organize itself in such a manner that the highpriority part of the codebook is sensitized to track the local (specific) characteristics of the input image. This method improves the coding efficiency and provides a perceptually more consistent image quality throughout all areas of the restructured image. Simulation results show that for the test color images bit rates in the range of 0.15–0.25 bits per pixel with a signal-to-noise ratio around 27–30 dB can be achieved.

Radiographic image sequence coding using two-stage adaptive vector quantization

A two-stage adaptive vector quantization scheme for radiographic image sequence coding is introduced. Each frame in the sequence is first decomposed into a set of vectors, corresponding to nonoverlapping spatially contiguous block of pixels. A codebook is generated using a training set of vectors drawn from the sequence. Each vector is then encoded by the label representing the closest codeword of the codebook, and the label values in a frame label map memory at both ends of the communication channel. The changes occurring in the radiographic image sequences can be categorized into two types: those due to body motion and those due to the injected contrast dye material. In the second scheme proposed, encoding is performed in two stages. In the first stage, the labels of corresponding vectors from consecutive frames are compared and the frame label map memory is replenished (updated). This stage is sufficient to tack the changes caused by patient motions but not due to the injected contrast dye material. The resulting residual error vectors after the first stage coding are calculated for the latter changes and are further encoded by a second codebook, which is updated on a frame-to-frame basis.

Interframe coding of moving image sequences

A new interframe coding technique is proposed, where a two-dimensional Hadamard transform is applied on each sub-block of successive frames, and an adaptive vector quantization scheme is applied along the transformed blocks of the successive frames. The performance of the algorithm is evaluated by computer simulation on a sequence of moving images.