Dense Photometric Stereo: A Markov Random Field Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
GPU-friendly rendering for illumination adjustable images
Image Communication
Data-intensive image based relighting
Proceedings of the 5th international conference on Computer graphics and interactive techniques in Australia and Southeast Asia
Parallelization of cellular neural networks on GPU
Pattern Recognition
Uniformly sampling multi-resolution analysis for image-based relighting
Journal of Visual Communication and Image Representation
Real-time diffuse global illumination using radiance hints
Proceedings of the ACM SIGGRAPH Symposium on High Performance Graphics
Advanced textural representation of materials appearance
SIGGRAPH Asia 2011 Courses
International Journal of Computer Applications in Technology
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In image-based relighting, a pixel is associated with a number of sampled radiance values. This paper presents a two-level compression method. In the first level, the plenoptic property of a pixel is approximated by a spherical radial basis function (SRBF) network. That means that the spherical plenoptic function of each pixel is represented by a number of SRBF weights. In the second level, we apply a wavelet-based method to compress these SRBF weights. To reduce the visual artifact due to quantization noise, we develop a constrained method for estimating the SRBF weights. Our proposed approach is superior to JPEG, JPEG2000, and MPEG. Compared with the spherical harmonics approach, our approach has a lower complexity, while the visual quality is comparable. The real-time rendering method for our SRBF representation is also discussed.