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Texture Compression using Wavelet Decomposition
Author(s) -
Mavridis Pavlos,
Papaioannou Georgios
Publication year - 2012
Publication title -
computer graphics forum
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.578
H-Index - 120
eISSN - 1467-8659
pISSN - 0167-7055
DOI - 10.1111/j.1467-8659.2012.03203.x
Subject(s) - texture compression , computer science , data compression , image compression , haar wavelet , wavelet transform , discrete wavelet transform , fractal transform , quantization (signal processing) , artificial intelligence , data compression ratio , computer vision , transform coding , block truncation coding , compression (physics) , wavelet , algorithm , discrete cosine transform , image processing , image (mathematics) , materials science , composite material
In this paper we introduce a new fixed‐rate texture compression scheme based on the energy compaction properties of a modified Haar transform. The coefficients of this transform are quantized and stored using standard block compression methods, such as DXTC and BC7, ensuring simple implementation and very fast decoding speeds. Furthermore, coefficients with the highest contribution to the final image are quantized with higher accuracy, improving the overall compression quality. The proposed modifications to the standard Haar transform, along with a number of additional optimizations, improve the coefficient quantization and reduce the compression error. The resulting method offers more flexibility than the currently available texture compression formats, providing a variety of additional low bitrate encoding modes for the compression of grayscale and color textures.