Stochastic progressive photon mapping(SPPM)is one of the important global illumination methods in computer graphics.It can simulate caustics and specular-diffuse-specular lighting effects efficiently.However,as a bias...Stochastic progressive photon mapping(SPPM)is one of the important global illumination methods in computer graphics.It can simulate caustics and specular-diffuse-specular lighting effects efficiently.However,as a biased method,it always suffers from both bias and variance with limited iterations,and the bias and the variance bring multi-scale noises into SPPM renderings.Recent learning-based methods have shown great advantages on denoising unbiased Monte Carlo(MC)methods,but have not been leveraged for biased ones.In this paper,we present the first learning-based method specially designed for denoising-biased SPPM renderings.Firstly,to avoid conflicting denoising constraints,the radiance of final images is decomposed into two components:caustic and global.These two components are then denoised separately via a two-network framework.In each network,we employ a novel multi-residual block with two sizes of filters,which significantly improves the model’s capabilities,and makes it more suitable for multi-scale noises on both low-frequency and high-frequency areas.We also present a series of photon-related auxiliary features,to better handle noises while preserving illumination details,especially caustics.Compared with other state-of-the-art learning-based denoising methods that we apply to this problem,our method shows a higher denoising quality,which could efficiently denoise multi-scale noises while keeping sharp illuminations.展开更多
Photon mapping can simulate some special effects efficiently such as shadows and caustics. Photon mapping runs in two phases： the photon map generating phase and the radiance estimation phase. In this paper, we focus...Photon mapping can simulate some special effects efficiently such as shadows and caustics. Photon mapping runs in two phases： the photon map generating phase and the radiance estimation phase. In this paper, we focus on the bandwidth selection process in the second phase, as it can affect the final quality significantly. Poor results with noise arise if few photons are collected, while bias appears if a large number of photons are collected. In order to solve this issue, we propose an adaptive radiance estimation solution to obtain trade-offs between noise and bias by changing the number of neighboring photons and the shape of the collected area according to the radiance gradient. Our approach can be applied in both the direct and the indirect illumination computation. Finally, experimental results show that our approach can produce smoother quality while keeping the high frequency features perfectly compared with the original photon mapping algorithm.展开更多
Photon mapping is a global illumination algorithm which is composed of two steps： photon tracing and photon searching. During photon searching step, each shading point needs to search the photon-tree to find k-neighb...Photon mapping is a global illumination algorithm which is composed of two steps： photon tracing and photon searching. During photon searching step, each shading point needs to search the photon-tree to find k-neighbouring photons for reflected radiance estimation. As the number of shading points and the size of photon-tree are dramatically large, the photon searching step is time consuming. We propose a parallel photon searching algorithm by using radiance estimation approach for coherent shading points on the Intel Many Integrated Core （MIC） Architecture. In order to efficiently use single instruction multiple data （SIMD） units, shading points are clustered by similarity first （every cluster contains 16 shading-points）, and an initial neighbouring scope is searched from the photon-tree for each cluster. Then we use 16-wide SIMD units by performing k-NN searching from the initial neighbouring scope for those 16 shading-points in a cluster in parallel. We use the method to simulate some global illumination scenes on Intel Xeon processors and Intel Xeon Phi^TM coprocessors. The comparison results with existing photon mapping techniques indicate that our method gives significant improvement in speed with the same accuracy.展开更多
Photon mapping is a widely used technique for global illumination rendering. In the density estimation step of photon mapping, the indirect radiance at a shading point is estimated through a filtering process using ne...Photon mapping is a widely used technique for global illumination rendering. In the density estimation step of photon mapping, the indirect radiance at a shading point is estimated through a filtering process using nearby stored photons; an isotropic filtering kernel is usually used. However,using an isotropic kernel is not always the optimal choice, especially for cases when eye paths intersect with surfaces with anisotropic BRDFs. In this paper,we propose an anisotropic filtering kernel for density estimation to handle such anisotropic eye paths.The anisotropic filtering kernel is derived from the recently introduced anisotropic spherical Gaussian representation of BRDFs. Compared to conventional photon mapping, our method is able to reduce rendering errors with negligible additional cost when rendering scenes containing anisotropic BRDFs.展开更多
Global illumination is the core part of photo-realistic rendering. The photon mapping algorithm is an effective method for computing global illumination with its obvious advantage of caustic and color bleeding renderi...Global illumination is the core part of photo-realistic rendering. The photon mapping algorithm is an effective method for computing global illumination with its obvious advantage of caustic and color bleeding rendering. It is an active research field that has been developed over the past two decades. The deficiency of precise details and efficient rendering are still the main challenges of photon mapping. This report reviews recent work and classifies it into a set of categories including radiance estimation, photon relaxation, photon tracing, progressive photon mapping, and parallel methods. The goals of our report are giving readers an overall introduction to photon mapping and motivating further research to address the limitations of existing methods.展开更多
The properties of two-dimensional (2D) photonic crystals (PCs) composed of germanium (Ge) are discussed. We investigate polarization-dependent photonic band diagrams (transverse electric and transverse magnetic polari...The properties of two-dimensional (2D) photonic crystals (PCs) composed of germanium (Ge) are discussed. We investigate polarization-dependent photonic band diagrams (transverse electric and transverse magnetic polarizations), gap maps, surface plots, contour maps, etc. for 2D PCs with Ge rods in air and vice versa for two different lattices geometries, namely hexagonal and honeycomb lattices. The obtained graphs for the four possible combinations are presented in this paper. All the graphs depict clear photonic band gaps. The conditions for the largest TE and TM band gaps are described. The honeycomb lattice of Ge rods in air background offers a large complete photonic band gap Δω/ωm greater than 8% (for rod radius of r = 0.2 μm). Using these data, new Ge based photonic devices can be fabricated to confine, control and manipulate light in a more useful way.展开更多
基金This work was partially supported by the National Key Research and Development Program of China under Grant No.2017YFB0203000the National Natural Science Foundation of China under Grant Nos.61802187,61872223,and 61702311the Natural Science Foundation of Jiangsu Province of China under Grant No.BK20170857.
文摘Stochastic progressive photon mapping(SPPM)is one of the important global illumination methods in computer graphics.It can simulate caustics and specular-diffuse-specular lighting effects efficiently.However,as a biased method,it always suffers from both bias and variance with limited iterations,and the bias and the variance bring multi-scale noises into SPPM renderings.Recent learning-based methods have shown great advantages on denoising unbiased Monte Carlo(MC)methods,but have not been leveraged for biased ones.In this paper,we present the first learning-based method specially designed for denoising-biased SPPM renderings.Firstly,to avoid conflicting denoising constraints,the radiance of final images is decomposed into two components:caustic and global.These two components are then denoised separately via a two-network framework.In each network,we employ a novel multi-residual block with two sizes of filters,which significantly improves the model’s capabilities,and makes it more suitable for multi-scale noises on both low-frequency and high-frequency areas.We also present a series of photon-related auxiliary features,to better handle noises while preserving illumination details,especially caustics.Compared with other state-of-the-art learning-based denoising methods that we apply to this problem,our method shows a higher denoising quality,which could efficiently denoise multi-scale noises while keeping sharp illuminations.
基金This work was partly supported by the National Natural Science Foundation of China under Grant Nos. 61472224 and 61472225, the National High Technology Research and Development 863 Program of China under Grant No. 2012AAOIA306, the Special Funding of Independent Innovation and Transformation of Achievements in Shandong Province of China under Grant No. 2014ZZCX08201, Shandong Key Research and Development Program under Grant No, 2015GGX106006, Young Scholars Program of Shandong University under Grant No. 2015WLJH41, and the Special Funds of Taishan Scholar Construction Project.
文摘Photon mapping can simulate some special effects efficiently such as shadows and caustics. Photon mapping runs in two phases： the photon map generating phase and the radiance estimation phase. In this paper, we focus on the bandwidth selection process in the second phase, as it can affect the final quality significantly. Poor results with noise arise if few photons are collected, while bias appears if a large number of photons are collected. In order to solve this issue, we propose an adaptive radiance estimation solution to obtain trade-offs between noise and bias by changing the number of neighboring photons and the shape of the collected area according to the radiance gradient. Our approach can be applied in both the direct and the indirect illumination computation. Finally, experimental results show that our approach can produce smoother quality while keeping the high frequency features perfectly compared with the original photon mapping algorithm.
基金This work was partly supported by the National Natural Science Foundation of China under Grant Nos. 61472224, 61472225,the National High Technology Research and Development 863 Program of China under Grant No. 2012AA01A306, the National Key Technology Research and Development Prograxn of China under Grant No. 2013BAH39F02, the Special Funding of Independent Innovation and Transformation of Achievements in Shandong Province of China under Grant No. 2014ZZCX08201, and the Special Funds of Taishan Scholar Construction Project of China.
文摘Photon mapping is a global illumination algorithm which is composed of two steps： photon tracing and photon searching. During photon searching step, each shading point needs to search the photon-tree to find k-neighbouring photons for reflected radiance estimation. As the number of shading points and the size of photon-tree are dramatically large, the photon searching step is time consuming. We propose a parallel photon searching algorithm by using radiance estimation approach for coherent shading points on the Intel Many Integrated Core （MIC） Architecture. In order to efficiently use single instruction multiple data （SIMD） units, shading points are clustered by similarity first （every cluster contains 16 shading-points）, and an initial neighbouring scope is searched from the photon-tree for each cluster. Then we use 16-wide SIMD units by performing k-NN searching from the initial neighbouring scope for those 16 shading-points in a cluster in parallel. We use the method to simulate some global illumination scenes on Intel Xeon processors and Intel Xeon Phi^TM coprocessors. The comparison results with existing photon mapping techniques indicate that our method gives significant improvement in speed with the same accuracy.
基金supported by the National High-tech R&D Program of China (No. 2012AA011802)the National Natural Science Foundation of China (No. 61170153)
文摘Photon mapping is a widely used technique for global illumination rendering. In the density estimation step of photon mapping, the indirect radiance at a shading point is estimated through a filtering process using nearby stored photons; an isotropic filtering kernel is usually used. However,using an isotropic kernel is not always the optimal choice, especially for cases when eye paths intersect with surfaces with anisotropic BRDFs. In this paper,we propose an anisotropic filtering kernel for density estimation to handle such anisotropic eye paths.The anisotropic filtering kernel is derived from the recently introduced anisotropic spherical Gaussian representation of BRDFs. Compared to conventional photon mapping, our method is able to reduce rendering errors with negligible additional cost when rendering scenes containing anisotropic BRDFs.
基金Project supported by the National Natural Science Foundation of China(Nos.61472224 and 61472225)the Young Scholars Program of Shandong University,China(No.2015WLJH41)+2 种基金the Shandong Key Research and Development Program,China(No.2015GGX106006)the Special Funding of Independent Innovation and Transformation of Achievements in Shandong Province of China(No.2014ZZCX08201)the Special Funds of Taishan Scholar Construction Project,China
文摘Global illumination is the core part of photo-realistic rendering. The photon mapping algorithm is an effective method for computing global illumination with its obvious advantage of caustic and color bleeding rendering. It is an active research field that has been developed over the past two decades. The deficiency of precise details and efficient rendering are still the main challenges of photon mapping. This report reviews recent work and classifies it into a set of categories including radiance estimation, photon relaxation, photon tracing, progressive photon mapping, and parallel methods. The goals of our report are giving readers an overall introduction to photon mapping and motivating further research to address the limitations of existing methods.
文摘The properties of two-dimensional (2D) photonic crystals (PCs) composed of germanium (Ge) are discussed. We investigate polarization-dependent photonic band diagrams (transverse electric and transverse magnetic polarizations), gap maps, surface plots, contour maps, etc. for 2D PCs with Ge rods in air and vice versa for two different lattices geometries, namely hexagonal and honeycomb lattices. The obtained graphs for the four possible combinations are presented in this paper. All the graphs depict clear photonic band gaps. The conditions for the largest TE and TM band gaps are described. The honeycomb lattice of Ge rods in air background offers a large complete photonic band gap Δω/ωm greater than 8% (for rod radius of r = 0.2 μm). Using these data, new Ge based photonic devices can be fabricated to confine, control and manipulate light in a more useful way.
