Noise-resistant fitting for spherical harmonics

IEEE Transactions on Visualization and Computer Graphics
Ping-Man LamTien-Tsin Wong

Abstract

Spherical harmonic (SH) basis functions have been widely used for representing spherical functions in modeling various illumination properties. They can compactly represent low-frequency spherical functions. However, when the unconstrained least square method is used for estimating the SH coefficients of a hemispherical function, the magnitude of these SH coefficients could be very large. Hence, the rendering result is very sensitive to quantization noise (introduced by modern texture compression like S3TC, IEEE half float data type on GPU, or other lossy compression methods) in these SH coefficients. Our experiments show that, as the precision of SH coefficients is reduced, the rendered images may exhibit annoying visual artifacts. To reduce the noise sensitivity of the SH coefficients, this paper first discusses how the magnitude of SH coefficients affects the rendering result when there is quantization noise. Then, two fast fitting methods for estimating the noise-resistant SH coefficients are proposed. They can effectively control the magnitude of the estimated SH coefficients and, hence, suppress the rendering artifacts. Both statistical and visual results confirm our theory.

References

Feb 6, 2008·IEEE Transactions on Neural Networks·C S LeungL W Chan
Jan 1, 1997·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·R L JoshiR H Bamberger

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Citations

Jul 12, 2007·IEEE Transactions on Visualization and Computer Graphics·Man-Kang LeungPheng-Ann Heng
Nov 17, 2009·IEEE Transactions on Visualization and Computer Graphics·Ping-Man LamTien-Tsin Wong
Oct 14, 2009·IEEE Transactions on Neural Networks·Tze-Yiu HoTien-Tsin Wong

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