A fast full search equivalent encoding algorithm for image vector quantization based on the WHT and a LUT

The application of vector quantization has been constrained to a great deal since its encoding process is very heavy. This paper presents a fast encoding algorithm called the double feature-ordered partial codebook search (DFPS) algorithm for image vector quantization. The DFPS algorithm uses the Wa...

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Bibliographic Details
Main Authors: Chul-hyung Ryu, Sung-woong Ra
Format: Conference Proceeding
Language:English
Subjects:
Compaction
Computational complexity
Decoding
Discrete wavelet transforms
Distortion measurement
Encoding
Image coding
Research and development
Table lookup
Vector quantization
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Summary:The application of vector quantization has been constrained to a great deal since its encoding process is very heavy. This paper presents a fast encoding algorithm called the double feature-ordered partial codebook search (DFPS) algorithm for image vector quantization. The DFPS algorithm uses the Walsh-Hadamard transform (WHT) for energy compaction and a look-up table (LUT) for fast reference. The simulation results show that with elaborate preprocessing and memory cost within a feasible level, the proposed DFPS algorithm is faster than other existing search algorithms. Compared with the exhaustive full search (EFS) algorithm, the DFPS algorithm reduces the computational complexity by 97.0% to 97.8% for a codebook size of 256 while maintaining the same encoding quality as that of the EFS algorithm.
DOI:10.1109/IWSOC.2005.7