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A Hybrid Texture Coding Method for Fast Texture Mapping
Author(s) -
Li Cui,
HyunGyu Kim,
Euee S. Jang
Publication year - 2016
Publication title -
journal of computing science and engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.172
H-Index - 16
eISSN - 2093-8020
pISSN - 1976-4677
DOI - 10.5626/jcse.2016.10.2.68
Subject(s) - computer science , texture (cosmology) , coding (social sciences) , artificial intelligence , texture compression , texture synthesis , computer vision , pattern recognition (psychology) , image texture , image (mathematics) , image processing , mathematics , statistics
An efficient texture compression method is proposed based on a block matching process between the current block and the previously encoded blocks. Texture mapping is widely used to improve the quality of rendering results in real-time applications. For fast texture mapping, it is important to find an optimal trade-off between compression efficiency and computational complexity. Low-complexity methods (e.g., ETC1 and DXT1) have often been adopted in real-time rendering applications because conventional compression methods (e.g., JPEG) achieve a high compression ratio at the cost of high complexity. We propose a block matching-based compression method that can achieve a higher compression ratio than ETC1 and DXT1 while maintaining computational complexity lower than that of JPEG. Through a comparison between the proposed method and existing compression methods, we confirm our expectations on the performance of the proposed method.

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