發(fā)布時(shí)間：2018-07-06 14:13

  本文選題：全局光照 + 光子映射��； 參考：《山東大學(xué)》2016年博士論文

【摘要】：數(shù)字動(dòng)漫與影視產(chǎn)業(yè)蓬勃發(fā)展,虛擬現(xiàn)實(shí)技術(shù)也逐漸走入我們的生活中。為了帶給人們更加真實(shí)的觀影和體驗(yàn)效果,高度真實(shí)感繪制技術(shù)在影視動(dòng)漫游戲等作品的制作中發(fā)揮著越來越重要的作用。優(yōu)秀電影和動(dòng)漫作品的不斷涌出離不開繪制技術(shù)的不斷發(fā)展,更加真實(shí)的繪制效果使動(dòng)漫電影的作品質(zhì)量得到質(zhì)的飛躍。然而高度真實(shí)感繪制算法是計(jì)算復(fù)雜的,尤其是三維動(dòng)漫和特效電影作品的場景設(shè)計(jì)都包含大量的模型,材質(zhì),燈光等,這使得在這些作品的制作中繪制成為最為耗時(shí)的階段之一。因此,研究逼真而高效的繪制算法和充分利用計(jì)算硬件計(jì)算能力的并行繪制算法,提升算法計(jì)算效果和計(jì)算速度,是計(jì)算機(jī)圖形學(xué)和繪制領(lǐng)域最重要的研究課題之一。全局光照算法是真實(shí)感繪制中核心的部分,全局光照是指除了計(jì)算物體表面從光源接收到的光照外,還要計(jì)算場景中物體相互作用后到達(dá)物體表面的光照,以及物體自身所發(fā)出的光照。在計(jì)算機(jī)圖形學(xué)中,通常使用繪制方程來求解全局光照問題�，F(xiàn)實(shí)中,我們能看到一個(gè)物體,是因?yàn)檫@個(gè)物體或反射或自發(fā)光射出的光能進(jìn)入了我們的眼睛。繪制方程即是描述了在物體表面上的一個(gè)點(diǎn)處所有對它產(chǎn)生照射的光能和在這一點(diǎn)上某個(gè)出射方向出射光能的關(guān)系。光子映射算法通過求解繪制方程完成繪制,是一種多遍繪制的全局光照算法。第一遍繪制是光子追蹤過程,光子追蹤的目的是記錄在漫反射表面的光照信息,從場景的光源處發(fā)射光子,光子是帶有一定光通量的最小單位。光子在場景中反彈和表面發(fā)生交互,并在非鏡面表面保存,最后產(chǎn)生光子圖(Photon Map)。光子圖是光子映射的中間結(jié)果,需要緩存到內(nèi)存中,一般使用KD-樹組織存儲(chǔ)。第二遍繪制是光線追蹤和輻射亮度估計(jì)過程。按照光線追蹤流程,從屏幕空間發(fā)射光線來計(jì)算屏幕空間像素顏色,追蹤這些光線,在光線與幾何相交的著色點(diǎn)處收集一定數(shù)目的最近鄰光子計(jì)算出射輻射亮度并完成著色計(jì)算。本文首先對光子映射算法的研究現(xiàn)狀進(jìn)行總結(jié)分析,將光子映射算法的優(yōu)化算法進(jìn)行分類,從輻射亮度估計(jì)優(yōu)化,光子分布優(yōu)化,光子圖生成優(yōu)化,漸進(jìn)式光子映射優(yōu)化和并行光子映射算法優(yōu)化這五個(gè)方面進(jìn)行劃分,總結(jié)各類方法的特點(diǎn)以及它們的優(yōu)缺點(diǎn)。并且從結(jié)果的平滑程度,特征保持,和內(nèi)存及繪制效率三個(gè)方面比較優(yōu)化程度。最后對光子映射算法未來的研究方向提出建議并根據(jù)光子映射算法中存在的問題開展研究。在光子映射算法中,通過收集最近鄰光子來估計(jì)著色點(diǎn)處的出射輻射亮度是計(jì)算中的核心步驟,同時(shí)由于光子的離散分布也引入了一定的偏差和噪聲。本文針對這一問題,提出了一種基于梯度的光子映射算法。利用光子分布的梯度檢查區(qū)分光照平滑表面和光照變化特征表面,在光照平滑的表面,計(jì)算的梯度值小,需要保持較大的搜索范圍以去除噪聲;而在光照變化的特征處,計(jì)算的梯度值大,需要自適應(yīng)地縮小光子搜索范圍和改變搜索范圍的形狀,使光子收集盡量不跨越特征范圍而減少偏差現(xiàn)象�；�于梯度的光子映射算法在收集光子過程中只增加梯度值計(jì)算和梯度值控制,計(jì)算簡單,不增加內(nèi)存使用,并且易于在當(dāng)前的光子映射算法的框架中實(shí)現(xiàn)和集成,同時(shí)可以獲得更優(yōu)的繪制效果。漸進(jìn)式光子映射算法有別于傳統(tǒng)的光子映射算法,它通過光子迭代發(fā)射實(shí)現(xiàn)無限大的光子計(jì)算,來解決傳統(tǒng)的光子映射算法無法保存超大光子圖的問題。由于需要大量的迭代計(jì)算次數(shù)達(dá)到繪制要求,計(jì)算時(shí)間長,本文提出了一種基于樣本消除的漸進(jìn)式光子映射算法,算法通過使用樣本處理的方法從光子分布中去除一定的噪聲從而達(dá)到優(yōu)化繪制效果,加速繪制效率的目的。算法的核心思想是在每一遍光子繪制中,加入一步使用光子消除處理光子圖的計(jì)算過程,并且在多次迭代中引入一顆全局的消除狀態(tài)樹保存和不斷更新消除的中間數(shù)據(jù)。消除狀態(tài)樹保存局部的光子分布密度和局部光子消除比例,并可以使?fàn)顟B(tài)樹的采樣點(diǎn)分布符合光子分布。在光子繪制過程,通過改進(jìn)樣本消除的計(jì)算使它適合光子繪制中不同的光子分布密度的消除,并不斷迭代完善狀態(tài)樹中保存的用于光子消除的光子分布信息,確保消除后剩余光子分布的準(zhǔn)確。同時(shí),基于消除狀態(tài)樹中局部光子消除信息,我們提出了光子消除的并行策略,將光子按包圍盒劃分并分塊處理,使光子消除的效率控制在可使用的范圍內(nèi)。通過狀態(tài)樹的維護(hù)和并行策略的優(yōu)化,基于樣本消除的漸進(jìn)式光子映射算法可以促進(jìn)漸進(jìn)式光子映射算法的加速收斂,同時(shí)保證光照分布的準(zhǔn)確性。除了使用優(yōu)化算法提高繪制效率,本文還提出一種在Intel眾核架構(gòu)(Many Integrated Core, MIC)上實(shí)現(xiàn)的并行光子映射算法,充分考慮協(xié)處理器的并行處理能力和16位浮點(diǎn)數(shù)寬度向量計(jì)算單元。在光子發(fā)射階段,每個(gè)光子初始化后都有不同的方向,采用單條光線并行地和場景樹求交的算法將光子追蹤過程部署在MIC協(xié)處理器并行加速。每個(gè)線程負(fù)責(zé)處理一條光線,將場景組織成四叉的BVH樹(Quad Bounding Volume Hierarchy Tree),使用向量計(jì)算單元并行計(jì)算單條光線和一個(gè)樹節(jié)點(diǎn)的四個(gè)孩子包圍盒并行求交。在第二步光子繪制階段,利用著色點(diǎn)之間的連貫性,使用向量計(jì)算單元并行地計(jì)算每個(gè)著色點(diǎn)的最近鄰光子搜索。首先將一組著色點(diǎn)按照相似性聚類。每個(gè)MIC協(xié)處理器線程負(fù)責(zé)處理一個(gè)著色點(diǎn)類,在一個(gè)著色點(diǎn)類內(nèi),首先為這個(gè)類搜索一個(gè)初始的最近鄰范圍,利用向量計(jì)算單元并行地在這一初始范圍內(nèi)為每個(gè)著色點(diǎn)挑選它的最近鄰光子,算法采用了數(shù)據(jù)直方圖統(tǒng)計(jì)的方式計(jì)算每個(gè)著色點(diǎn)的最近鄰搜索范圍。算法通過兩個(gè)不同階段的并行方案,將光子映射算法首次部署在搭載MIC協(xié)處理器的服務(wù)器上,達(dá)到精確計(jì)算的同時(shí)又取得了最優(yōu)的并行加速效率。本文研究基于光子映射的全局光照算法,在分析光子映射算法發(fā)展的基礎(chǔ)上,提出有效的優(yōu)化算法,提升光子映射算法的繪制效果和繪制效率。并提出了在IntelMIC架構(gòu)服務(wù)器上部署的并行光子映射算法,在未來的發(fā)展中,為繪制應(yīng)用在目前已有的超級計(jì)算機(jī)上的部署提供了研究基礎(chǔ)。
[Abstract]:Digital animation and film and television industry are booming, and virtual reality technology is gradually coming into our life. In order to bring people more real view and experience effect, highly realistic rendering technology plays a more and more important role in the production of film and television animation games. The continuous development of open drawing technology, more real rendering effect makes the quality of animation film works qualitatively. However, the highly realistic rendering algorithm is complex, especially the scene design of 3D animation and special effect film contains a large number of models, materials, lighting and so on, which makes the production of these works. It is one of the most time-consuming stages. Therefore, it is one of the most important research topics in the field of computer graphics and rendering to study realistic and efficient rendering algorithms and to make full use of the parallel rendering algorithm of computing hardware computing power and to improve the computational efficiency and computing speed. Global illumination algorithm is the core of the realistic rendering. Global illumination means that in addition to calculating the illumination received from the light source from the surface of the object, the illumination of the object's surface after the interaction of the objects in the scene and the illumination of the object itself are calculated. In computer graphics, the drawing equation is usually used to solve the whole illumination problem. In reality, we can see an object, It is because the light energy emitted by this object or reflection or self luminescence enters our eyes. The equation is to describe the light energy that irradiate it at a point on the surface of the object and the relationship between the emission of light energy at a certain ejection direction at this point. A global illumination algorithm plotted in multiple times. The first time is the process of photon tracing. The purpose of the photon tracing is to record the illumination information on the diffuse surface. The photon is emitted from the light source of the scene. The photon is the smallest unit with a certain luminous flux. The photon is bouncing in the scene and interacting with the surface, and is saved on the non mirror surface and finally produced. Photon Map. The photon map is the intermediate result of the photon mapping, which needs to be cached in memory, usually stored in the KD- tree. The second time is the process of ray tracing and radiance estimation. According to the ray tracing process, the screen space pixels color is calculated from the screen space, tracing the light and several of the light. A number of nearest neighbour photons are collected to calculate the radiance of the nearest neighbor photon and to complete the coloring calculation. Firstly, the research status of the photon mapping algorithm is summarized and analyzed, and the optimization algorithm of the photon mapping algorithm is classified, from the optimization of the radiance estimation, the optimization of photon distribution, the optimization of the photon map generation, and the gradual optimization. The five aspects of the optimization of the type photon mapping and the optimization of the parallel photon mapping algorithm are divided, and the characteristics of various methods and their advantages and disadvantages are summarized. The optimization degree is compared from the three aspects of the smoothness of the results, the retention of the features, the memory and the rendering efficiency. Finally, the future research direction of the photon mapping algorithm is proposed and the root is put forward. According to the problems in the photon mapping algorithm, in the photon mapping algorithm, the estimation of the emitted radiation brightness at the coloring point by collecting the nearest neighbor photons is the core step in the calculation, and a certain deviation and noise are introduced due to the discrete distribution of the photon. A gradient based method is proposed for this problem. The photon mapping algorithm uses the gradient examination of the photon distribution to distinguish the smooth surface of the light and the characteristic surface of the illumination change. In the smooth surface of the light, the calculated gradient value is small. It needs to keep a larger search range to remove the noise; and the calculated ladder value is large in the characteristics of the illumination change, and the photon search range needs to be narrowed adaptively. Change the shape of the search range so that the photon collection can reduce the deviation from the feature range as much as possible. The gradient based photon mapping algorithm only increases the gradient value calculation and gradient value control in the process of collecting photons, which is simple and does not increase the use of memory, and is easy to implement and integrate in the framework of the previous photon mapping algorithm. The progressive photon mapping algorithm is different from the traditional photon mapping algorithm, which realizes infinite photon calculation through the photon iterative emission to solve the problem that the traditional photon mapping algorithm can not save the ultra large photon map. For a long time, a progressive photon mapping algorithm based on sample elimination is proposed in this paper. The algorithm uses sample processing to remove certain noise from the photon distribution to optimize the rendering effect and accelerate the rendering efficiency. The core idea of the algorithm is to add one step to the photon elimination in each photon rendering. To deal with the calculation process of the photon map, and to introduce a global elimination state tree to save and update the intermediate data in many iterations. To eliminate the local photon distribution density and the local photon elimination ratio in the state tree, and to make the sampling point distribution of the state tree conform to the photon distribution. The calculation of the sample elimination makes it fit for the elimination of the photon distribution density in the photon drawing, and continuously iterates out the information of photon distribution used in the photon elimination in the state tree and ensures the accuracy of the elimination of the residual photon distribution. At the same time, we propose the photon elimination based on the elimination of information from the local photon in the state tree. The parallel strategy divides the photon into a bounding box and divides it into block processing to make the efficiency of the photon elimination within the available range. Through the maintenance of the state tree and the optimization of the parallel strategy, the progressive photon mapping algorithm based on the sample elimination can accelerate the accelerated convergence of the progressive photon mapping algorithm and ensure the accuracy of the illumination distribution. In addition to using the optimization algorithm to improve the rendering efficiency, this paper also proposes a parallel photon mapping algorithm implemented on the Intel Many Integrated Core (MIC), which fully considers the parallel processing capability of the coprocessor and the 16 bit floating-point width vector computing unit. Each photon is initialized differently at the photon emission stage. The direction, using a single ray parallel algorithm with the scene tree, deploys the photon tracing process on the MIC coprocessor parallel acceleration. Each thread is responsible for processing a ray of light, organizing the scene into a four fork BVH tree (Quad Bounding Volume Hierarchy Tree), using a vector computing unit to compute a single ray and a tree node of four. In the second step photon drawing stage, in the second step photon drawing stage, using the coherence between the coloring points, the vector computing unit is used to compute the nearest neighbor photon search in each coloring point. First, a group of coloring points is clustered according to the similarity. Each MIC coprocessor thread handles a coloring point class and is in a coloring point. In the class, we first search for an initial nearest neighbor range for this class, and use the vector computing unit to select the nearest neighbor photon for each coloring point in this initial range. The algorithm uses the method of data histogram to calculate the nearest neighbor search range of each colored point. The algorithm passes through two different stages of the parallel square. In the case, the photon mapping algorithm is first deployed on the server carrying the MIC coprocessor to achieve accurate calculation and achieve the optimal parallel acceleration efficiency. This paper studies the global illumination algorithm based on photon mapping. On the basis of the analysis of the development of the photon mapping algorithm, an effective optimization algorithm is proposed to improve the photon mapping algorithm. The effect and efficiency of drawing are drawn. A parallel photon mapping algorithm is proposed on the IntelMIC architecture server. In the future development, it provides the research foundation for the deployment of the application on the existing supercomputers.
【學(xué)位授予單位】：山東大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2016
【分類號】：TP391.41

【相似文獻(xiàn)】

相關(guān)期刊論文 前10條

1 李偉偉;董杰;李海霞;張桂連;;多光源實(shí)時(shí)全局光照算法的實(shí)現(xiàn)[J];吉林大學(xué)學(xué)報(bào)(信息科學(xué)版);2011年02期

2 吳向陽;柴學(xué)梁;王毅剛;張龍;;利用形狀因子采樣的實(shí)時(shí)全局光照繪制[J];計(jì)算機(jī)輔助設(shè)計(jì)與圖形學(xué)學(xué)報(bào);2011年06期

3 孫濟(jì)洲,吳奇,邢昌玉,ＧｒｉｍｓｄａｌｅＲＬ;一種求解全局光照的分層遮擋測試算法(英文)[J];Transactions of Tianjin University;1998年01期

4 徐慶,魏尊策,陳實(shí),田欣梅,孫濟(jì)洲;一種面向并行實(shí)現(xiàn)的全局光照算法[J];計(jì)算機(jī)應(yīng)用研究;2001年03期

5 邢連萍;徐慶;;基于信息熵的蒙特卡羅全局光照的自適應(yīng)抽樣[J];計(jì)算機(jī)工程;2007年21期

6 汪波;李毅;;基于預(yù)計(jì)算輻射傳遞的全局光照技術(shù)[J];計(jì)算機(jī)應(yīng)用;2010年12期

7 李瑞瑞;秦開懷;張一天;;包含反射、折射和焦散效果的全局光照快速繪制方法[J];計(jì)算機(jī)輔助設(shè)計(jì)與圖形學(xué)學(xué)報(bào);2013年08期

8 王輝;劉學(xué)慧;吳恩華;;利用球諧方法分散計(jì)算場景的全局光照[J];計(jì)算機(jī)輔助設(shè)計(jì)與圖形學(xué)學(xué)報(bào);2007年05期

9 王莉莉;楊崢;馬志強(qiáng);趙沁平;;基于梯度圖的微結(jié)構(gòu)表面全局光照實(shí)時(shí)繪制[J];軟件學(xué)報(bào);2011年10期

10 孫其民,吳恩華;全局光照環(huán)境中的逆向繪制[J];軟件學(xué)報(bào);2003年10期

相關(guān)會(huì)議論文 前1條

1 劉魯男;;三維特技鏡頭的制作——“真實(shí)”的輕松再現(xiàn)[A];2011中國電影電視技術(shù)學(xué)會(huì)影視技術(shù)文集[C];2011年

相關(guān)博士學(xué)位論文 前5條

1 康春萌;基于光子映射的全局光照技術(shù)研究[D];山東大學(xué);2016年

2 李瑞瑞;反射、折射、焦散的全局光照加速繪制研究[D];清華大學(xué);2014年

3 任重;基于預(yù)計(jì)算的交互式全局光照明研究[D];浙江大學(xué);2007年

4 王貝貝;基于點(diǎn)緩存全局光照技術(shù)的研究[D];山東大學(xué);2014年

5 孫鑫;可變材質(zhì)的交互級全局光照明繪制算法的研究[D];浙江大學(xué);2008年

相關(guān)碩士學(xué)位論文 前10條

1 嚴(yán)俊;GPU上的交互式全局光照渲染系統(tǒng)[D];浙江大學(xué);2015年

2 黃楊昱;基于實(shí)時(shí)全局光照的3D繪制引擎研究和開發(fā)[D];北京化工大學(xué);2015年

3 馬存鎖;基于全局光照算法的實(shí)時(shí)渲染組件研究與應(yīng)用[D];電子科技大學(xué);2015年

4 秦學(xué);基于輻射度回歸函數(shù)的可交互全局光照渲染改進(jìn)[D];上海交通大學(xué);2015年

5 孫文杰;醫(yī)學(xué)圖像的三維可視化系統(tǒng)研究[D];浙江工業(yè)大學(xué);2015年

6 金師豪;多光繪制框架下光澤場景的高效繪制[D];浙江大學(xué);2016年

7 孟祥雨;基于光子映射的分布式全局光照計(jì)算方法研究[D];山東大學(xué);2016年

8 張桂連;室內(nèi)實(shí)時(shí)全局光照技術(shù)研究[D];山東師范大學(xué);2009年

9 楚夢渝;基于GPU的漸進(jìn)式光子松弛[D];浙江大學(xué);2014年

10 朱元龍;Light Propagation Volume全局光照算法的研究[D];杭州電子科技大學(xué);2014年

，

本文編號：2103045