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Related Experiment Videos

Noise-resistant fitting for spherical harmonics.

Ping-Man Lam1, Chi-Sing Leung, Tien-Tsin Wong

  • 1Department of Electronic Engineering, City University of Hong Kong, Kowloon. lam.jacky@student.cityu.edu.hk

IEEE Transactions on Visualization and Computer Graphics
|March 3, 2006
PubMed
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This study addresses noise sensitivity in spherical harmonic (SH) rendering. New methods reduce SH coefficient magnitudes, suppressing visual artifacts caused by quantization noise in computer graphics.

Area of Science:

  • Computer Graphics
  • Image Processing
  • Applied Mathematics

Background:

  • Spherical harmonic (SH) basis functions are crucial for representing spherical functions in illumination modeling.
  • Unconstrained least squares estimation of SH coefficients for hemispherical functions can lead to large coefficient magnitudes.
  • Large SH coefficient magnitudes increase sensitivity to quantization noise from lossy compression, causing visual artifacts in rendered images.

Purpose of the Study:

  • To analyze the impact of SH coefficient magnitude on rendering quality under quantization noise.
  • To develop fast, noise-resistant methods for estimating SH coefficients.
  • To suppress rendering artifacts caused by quantization noise in computer graphics.

Main Methods:

  • Investigated the relationship between SH coefficient magnitude and rendering artifacts due to quantization noise.

Related Experiment Videos

  • Proposed two novel, fast fitting methods for estimating noise-resistant SH coefficients.
  • Controlled the magnitude of estimated SH coefficients to mitigate noise sensitivity.

    • Main Results:

    • Demonstrated that large SH coefficients amplify the negative effects of quantization noise.
    • The proposed methods effectively controlled SH coefficient magnitudes, significantly suppressing rendering artifacts.
    • Experimental results, both statistical and visual, validated the effectiveness of the noise-resistant estimation techniques.

    Conclusions:

    • The magnitude of SH coefficients is a critical factor influencing rendering quality in the presence of quantization noise.
    • The developed fast fitting methods offer a robust solution for generating noise-resistant SH coefficients.
    • These methods effectively reduce visual artifacts, improving the reliability of SH-based rendering with compressed data.