최소 단어 이상 선택하여야 합니다.
최대 10 단어까지만 선택 가능합니다.
다음과 같은 기능을 한번의 로그인으로 사용 할 수 있습니다.
NTIS 바로가기IEEE transactions on circuits and systems for video technology : a publication of the Circuits and Systems Society, v.10 no.8, 2000년, pp.1502 - 1513
Miaou, Shaou-Gang (Dept. of Electron. Eng., Chung Yuan Christian Univ., Chung Li, Taiwan) , Chung, Wen-Song
The gold-washing (GW) mechanism is an efficient on-line codebook refining technique for adaptive vector quantization (AVQ). However, the mechanism is essentially not suitable for hardware implementation. We propose a hardware-oriented GW-AVQ scheme based on the least-recently-used (LRU) strategy for codevector selection and the block-data-interpolation (BDI) algorithm for vector generation. We also present the VLSI architectures for the key components of GW-AVQ, including a 2-D systolic array (SABVQ) and a 1-D linear array (LABVQ) for full-search VQ, a pipeline BDI encoder (PBDI-E) and decoder (PBDI-D), and the LRU strategy. The SABVQ architecture can perform in O(k) time with O(N+N/k) area and O(k) I/O complexity; the LABVQ architecture reaches O(N) time, O(k+1) area, and O(k) I/O complexity, where k and N are the codevector dimension and codebook size, respectively. The PBDI architecture reaches O(1) time, O(k) area, and O(1) I/O complexity. The LRU architecture can perform in O(1) time, O(N) area and O(1) I/O complexity. With VHDL implementation, the maximum computational capacity of SABVQ, LABVQ, five-stage PBDI-E, PBDI-D, and LRU are 45, 2.8, 1667, 2232, and 246 (106 samples/s), respectively. These results are good enough for most of the practical image compression systems.
※ AI-Helper는 부적절한 답변을 할 수 있습니다.