Texture Compression using Wavelet Decomposition

  • Authors:
  • Pavlos Mavridis;Georgios Papaioannou

  • Affiliations:
  • Department of Informatics, Athens University of Economics & Business;Department of Informatics, Athens University of Economics & Business

  • Venue:
  • Computer Graphics Forum
  • Year:
  • 2012

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Abstract

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. © 2012 Wiley Periodicals, Inc.