An improved tree-structured codebook search algorithm for grayscale image compression
Fundamenta Informaticae
Fast codebook search algorithms based on tree-structured vector quantization
Pattern Recognition Letters
VQ Codebook Searching Algorithm Based on Correlation Property
Fundamenta Informaticae
Fast codebook search algorithm for vector quantization using sorting technique
Proceedings of the International Conference on Advances in Computing, Communication and Control
VQ Codebook Searching Algorithm Based on Correlation Property
Fundamenta Informaticae
An Improved Tree-Structured Codebook Search Algorithm for Grayscale Image Compression
Fundamenta Informaticae
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A new branch of tree-structured vector quantization is proposed to encode images. We call it the Dynamic Path Tree Structured Vector Quantization (DPTSVQ). Multi-path TSVQ uses a fixed number of paths to search the closest code-word; however, there is still plenty of room for improvement. To do way with the lack of flexibility fixed number of search paths, we propose DPTSVQ to take the place of multi-path TSVQ. With DPTSVQ, we try to improve multi-path TSVQ and make the number of search paths become variable. In this paper, we define a critical function to judge whether the number of search paths is growable for DPTSVQ. Our experimental results show that DPTSVQ is always faster than multi-path TSVQ with the image quality kept the same. DPTSVQ can reduce 50% of the encoding time, in general, from what is spent by multi-path TSVQ under the same image quality requirement. If such high image quality as that of full search is required, DPTSVQ remains more timesaving than multi-path TSVQ all the same.