Citation
Abstract
This article presents a study of a locally adaptive vector quantization (LAVQ) algorithm for data compression. This algorithm provides high-speed one-pass compression and is fully adaptable to any data source and does not require a priori knowledge of the source statistics. Therefore, LAVQ is a universal data compression algorithm. The basic algorithm and several modiffcations to improve performance are discussed. These modiffcations are nonlinear quantization, coarse quantization of the codebook, and lossless compression of the output. Performance of LAVQ on various images using Irreversible (lossy) coding is comparable to that of the Linde-Buzo-Gray algorithm, but LAVQ has a much higher speed; thus this algorithm has potential for real-time video compression. Unlike most other image compression algorithms, LAVQ preserves fine detail in images. LAVQ’s performance as a lossless data compression algorithm is comparable to that of Lempel-Ziv—based algorithms, but LAVQ uses far less memory during the coding process.
Details
- Volume
- 42-110
- Published
- August 15, 1992
- Pages
- 163–178
- File Size
- 909.6 KB