Rendering from compressed textures
SIGGRAPH '96 Proceedings of the 23rd annual conference on Computer graphics and interactive techniques
IEEE Computer Graphics and Applications
Texture compression using low-frequency signal modulation
Proceedings of the ACM SIGGRAPH/EUROGRAPHICS conference on Graphics hardware
iPACKMAN: high-quality, low-complexity texture compression for mobile phones
Proceedings of the ACM SIGGRAPH/EUROGRAPHICS conference on Graphics hardware
High-Dynamic-Range Still-Image Encoding in JPEG 2000
IEEE Computer Graphics and Applications
High dynamic range texture compression for graphics hardware
ACM SIGGRAPH 2006 Papers
High dynamic range texture compression
ACM SIGGRAPH 2006 Papers
Rendering from compressed high dynamic range textures on programmable graphics hardware
Proceedings of the 2007 symposium on Interactive 3D graphics and games
Image quality assessment: from error visibility to structural similarity
IEEE Transactions on Image Processing
A GPU-friendly method for high dynamic range texture compression using inverse tone mapping
GI '08 Proceedings of graphics interface 2008
DHTC: an effective DXTC-based HDR texture compression scheme
Proceedings of the 23rd ACM SIGGRAPH/EUROGRAPHICS symposium on Graphics hardware
A self-adaptive HVS-optimized texture compression algorithm
Proceedings of the 8th International Conference on Virtual Reality Continuum and its Applications in Industry
Technical Section: ftc-Floating precision texture compression
Computers and Graphics
Real-time high-dynamic range texture compression based on local fractal transform
Proceedings of the 24th Spring Conference on Computer Graphics
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We present a novel compression method for high dynamic range (HDR) textures, targeted for future graphics hardware. Identifying that the existing solutions provide either very high image quality or very simple hardware implementation, we aim to achieve both features in a single solution. Our approach improves upon an existing technique by incorporating a simple chrominance coding that allows overall image quality on par with the state of the art, but at a substantially lower encoding and decoding complexity. The end result is what we believe to be an excellent compromise between image quality and efficiency of hardware implementations. We evaluate our compression method using common test images and established HDR image quality metrics. Additionally, we complement these results with error measurements in the CIE L*a*b* color space in order to separately assess the quality of luminance and chrominance information.