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Related Experiment Video

Updated: Jul 8, 2026

Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters

Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters

Published on: June 18, 2021

Filtering and rendering of resolution-dependent reflectance models.

Ping Tan¹, Stephen Lin, Long Quan

¹Department of Computer Science and Engineering, HKUST, Clear Water Bay, Kowloon, Hong Kong. ptan@cse.ust.hk

IEEE Transactions on Visualization and Computer Graphics

|January 15, 2008

Summary

This study introduces a new framework for rendering surface reflectance that adapts to image resolution. It efficiently captures fine details often missed by traditional rendering methods.

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Measuring Spatially- and Directionally-varying Light Scattering from Biological Material

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Published on: May 20, 2013

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Last Updated: Jul 8, 2026

Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters

Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters

Published on: June 18, 2021

Measuring Spatially- and Directionally-varying Light Scattering from Biological Material

Measuring Spatially- and Directionally-varying Light Scattering from Biological Material

Published on: May 20, 2013

Area of Science:

Computer Graphics
Rendering Techniques
Surface Reflectance Modeling

Background:

Surface reflectance is resolution-dependent, posing challenges for accurate real-time rendering.
Conventional rendering methods often overlook fine reflectance details at varying resolutions.

Purpose of the Study:

To develop a framework for efficiently rendering resolution-dependent surface reflectance.
To represent complex reflectance as a mixture of conventional models for improved realism.

Main Methods:

Proposed a mixture model approach to represent resolution-dependent reflectance.
Utilized mipmaps to store mixture model parameters at multiple resolutions.
Developed a hardware-accelerated technique for nonlinear filtering of mipmapped parameters to minimize aliasing.

Main Results:

The framework efficiently renders reflectance effects across different resolutions.
Minimizes aliasing artifacts during mipmap filtering.
Enables real-time processing through hardware acceleration.

Conclusions:

The proposed mixture model filtering and rendering framework efficiently captures fine reflectance detail.
This approach enhances rendering realism by accounting for resolution-dependent effects.
The method is applicable to various parametric reflectance models and supports shadowing/masking.