학술논문

Fast-searching algorithm for vector quantization using modified multiple triangular inequality
Document Type
Conference
Source
2016 Conference on Technologies and Applications of Artificial Intelligence (TAAI) Technologies and Applications of Artificial Intelligence (TAAI), 2016 Conference on. :52-57 Nov, 2016
Subject
Computing and Processing
Robotics and Control Systems
Indexes
Image coding
Encoding
Aerospace electronics
Heuristic algorithms
Algorithm design and analysis
Decoding
Vector quantization (VQ)
Triangle inequality elimination (TIE)
Image compression
Language
ISSN
2376-6824
Abstract
This paper proposes a Modified Multiple Triangular Inequality Elimination (MMTIE) to further reduce the search number of candidate codevectors. The MMTIE adopts the same original search space as the MTIE scheme with the initial best-matched codevector selected by the Initial Index Code Assignment (IICA), and integrates the intersection rule of the Candidate Codevectors Group (CCG) scheme to further reduce the search space and find the best-matched candidate by table look-up operation in the coding stage. Since the IICA approach selects an initial best-matched codevector by exploiting the correlations of the neighboring blocks and the predefined CCG space is obtained from the off-line stage, the MMTIE algorithm achieves better coding efficiency than the original MTIE at a cost of extra memory. In addition, the proposed algorithm provides the same coding quality as the full search method. Experimental results demonstrate the effectiveness of the proposed scheme in comparison with our previous MTIE coding scheme.