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An RBF-based compression method for image-based relighting.

Chi-Sing Leung1, Tien-Tsin Wong, Ping-Man Lam

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

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|April 4, 2006
PubMed
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This study introduces a two-level compression method for image-based relighting, significantly improving efficiency and visual quality. The novel approach effectively compresses spherical plenoptic functions using spherical radial basis function networks and wavelets.

Area of Science:

  • Computer Graphics
  • Image Processing
  • Computational Imaging

Background:

  • Image-based relighting requires efficient representation of sampled radiance values per pixel.
  • Existing compression methods like JPEG and MPEG struggle with the complexity of plenoptic functions.

Purpose of the Study:

  • To develop a novel two-level compression method for image-based relighting.
  • To represent and compress the spherical plenoptic function of each pixel efficiently.
  • To reduce visual artifacts and maintain high visual quality.

Main Methods:

  • Approximation of pixel plenoptic properties using a spherical radial basis function (SRBF) network.
  • Wavelet-based compression of SRBF weights.
  • Development of a constrained method for SRBF weight estimation to mitigate quantization noise.

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Main Results:

  • The proposed method demonstrates superiority over JPEG, JPEG2000, and MPEG.
  • Achieves comparable visual quality to spherical harmonics but with lower computational complexity.
  • Enables real-time rendering of the SRBF representation.

Conclusions:

  • The two-level compression strategy offers an effective solution for image-based relighting.
  • The SRBF network combined with wavelet compression provides a high-quality, efficient representation.
  • The method presents a significant advancement in real-time relighting techniques.