【摘要】：真實(shí)感圖形繪制是計(jì)算機(jī)圖形學(xué)最重要的問題之一,而蒙特卡洛光線跟蹤是真實(shí)感圖形繪制中最主流的方法。該方法可以處理任意的光源類型、場(chǎng)景表達(dá)、紋理材質(zhì)、以及照相機(jī)設(shè)置。其缺點(diǎn)是計(jì)算復(fù)雜度較高,繪制性能較低。光路重用是提高蒙特卡洛光線跟蹤算法性能的重要途徑。通過重用一部分光路,可以將一條光路多次用于光能傳輸?shù)墓烙?jì),從而降低采樣的平均成本。另一方面,通過選擇較為重要的光路進(jìn)行重用,也可以實(shí)現(xiàn)一定程度的重要性采樣。根據(jù)重用光路采樣類型的不同,光路重用技術(shù)主要分為三類。由視線或光線方向生成的光路出發(fā),重用反向光路進(jìn)行連接,從而生成一條完整光路的,稱為雙向光路重用。將原光路采樣前半部分與另一條同向光路后半部分的光路進(jìn)行連接生成完整光路的,稱為單向光路重用。在二維圖像空間內(nèi),對(duì)光路采樣的估計(jì)結(jié)果,也就是著色值,進(jìn)行直接重用的,稱為圖像空間著色重用,也等價(jià)于對(duì)于整條光路的直接重用。本文系統(tǒng)地研究了蒙特卡洛光線跟蹤框架中的光路重用問題。三個(gè)主要工作涵蓋了三種不同類型的光路重用,分別是解決了雙向光路重用中的估計(jì)偏差問題,分析并減輕了單向光路重用中協(xié)方差對(duì)于估計(jì)方差的影響,以及利用二維圖像空間中光路采樣結(jié)果的一致性提出了高性能的毛發(fā)繪制算法。具體來說,本文包含如下內(nèi)容:(1)針對(duì)雙向光路重用,我們提出了 一個(gè)新的光子采集方法來替代之前光子映射算法中的密度估計(jì),從而得到無偏的繪制結(jié)果。我們會(huì)單獨(dú)處理每一個(gè)光子,將光子所代表的光線與進(jìn)行采集的視線相連,來形成一條完整的光路。這個(gè)連接可以被理解為一次俄羅斯輪盤事件,其成功概率是一個(gè)積分。由于這個(gè)連接的概率出現(xiàn)在最終貢獻(xiàn)估計(jì)的分母上,人們一直沒有高效的方法來避免在估計(jì)概率積分的同時(shí)引入偏差。因此我們提出了一個(gè)無偏的算法,利用一系列伯努利試樣來對(duì)這個(gè)概率積分的倒數(shù)進(jìn)行無偏估計(jì)。最終的方法是一個(gè)完備的無偏采樣技術(shù),并且可以被結(jié)合到廣泛的蒙特卡洛光能傳遞算法之中。(2)針對(duì)單向光路重用,我們研究了該類方法中光路重用的協(xié)方差對(duì)于最終繪制方差的影響。通過我們的分析可以發(fā)現(xiàn),在此類方法中估計(jì)方差由方差項(xiàng)以及協(xié)方差項(xiàng)兩部分組成。我們發(fā)現(xiàn)提高重建采樣率只能降低方差項(xiàng)部分,而對(duì)于協(xié)方差無能為力。我們也發(fā)現(xiàn)協(xié)方差項(xiàng)實(shí)際上表示了間接光照采樣在重建過程中被重用的程度。同一個(gè)間接光照采樣被越多的重建采樣所使用,其帶來的協(xié)方差項(xiàng)也就越顯著�；趯�(duì)于方差的分析,我們提出了一個(gè)自適應(yīng)生成間接光照采樣,從而降低協(xié)方差項(xiàng)的方法。我們將這個(gè)自適應(yīng)的方法應(yīng)用到間接光場(chǎng)重建算法以及軸對(duì)齊的圖像空間濾波算法之中,并顯著地減輕了繪制結(jié)果中的失真。(3)最后,針對(duì)圖像空間的著色重用,我們提出一個(gè)基于光錐的光線跟蹤技術(shù),來進(jìn)行毛發(fā)物體的高質(zhì)量繪制。通過將一個(gè)像素內(nèi)的所有光線聚合成一個(gè)光錐,我們實(shí)際上可以在這個(gè)光錐內(nèi)對(duì)于每個(gè)采樣的計(jì)算結(jié)果進(jìn)行重用,以此來降低毛發(fā)的纖細(xì)幾何所需要的巨量采樣。這樣一來不僅減少了采樣的計(jì)算代價(jià),也減少了半透明的毛發(fā)所需要的合成計(jì)算的代價(jià)。最后的結(jié)果是一個(gè)高效的光線跟蹤算法,可以生成與其他方法同質(zhì)量的繪制結(jié)果,同時(shí)顯著減少計(jì)算的時(shí)間。
[Abstract]:Realistic image drawing is one of the most important problems in computer graphics, and Monte Carlo ray tracing is the most important method in the drawing of real-sense graphics. The method can process any type of light source, scene representation, texture material, and camera settings. The method has the advantages that the calculation complexity is high, and the drawing performance is low. The optical path reuse is an important way to improve the performance of the Monte Carlo ray tracing algorithm. By reusing a portion of the optical path, an optical path can be used multiple times for the estimation of the optical energy transmission, thereby reducing the average cost of the sample. On the other hand, by selecting a more important optical path for reuse, it is also possible to realize a certain degree of importance sampling. According to the different sampling types of the reused optical path, the optical path reuse technology is mainly divided into three types. And the optical path generated by the line-of-sight or the optical line direction is used for connecting the back light path so as to generate a complete optical path, which is called a two-way optical path re-use. And the optical path of the half part of the front half part of the original optical path is connected with the optical path of the half part of the other co-directional light path to generate a complete optical path, and is called a one-way optical path reuse. In the two-dimensional image space, the estimation result of the optical path sampling, that is, the coloring value, is directly reused, called image space color reuse, and is also equivalent to the direct re-use of the whole optical path. In this paper, the problem of optical path re-use in the Monte Carlo ray tracing framework is studied systematically. The three main work covers three different types of optical path re-use, respectively solving the estimation deviation problem in the two-way optical path re-use, analyzing and reducing the influence of the covariance on the estimation variance in the one-way optical path re-use, And a high-performance hair drawing algorithm is provided by utilizing the consistency of the light path sampling results in the two-dimensional image space. In particular, this paper includes the following contents: (1) For bi-directional optical path re-use, we propose a new photon collection method to replace the density estimation in the previous photon mapping algorithm, so as to obtain an unbiased drawing result. We will process each photon separately, and connect the light represented by the photon with the line of sight to be collected to form a complete optical path. This connection can be understood as a Russian roulette event whose success probability is an integral. Since the probability of this connection appears on the denominator of the final contribution estimate, there has been no efficient way to avoid introducing a deviation while estimating the probability integral. So we put forward an unbiased algorithm that uses a series of Bernoulli samples to unbiased estimate the reciprocal of this probability integral. The final approach is a complete unbiased sampling technique and can be incorporated into a wide range of Monte Carlo radiosity algorithms. (2) For one-way optical path re-use, we have studied the influence of the covariance of the optical path re-use on the final drawing variance in this kind of method. By our analysis it can be found that, in such a method, the estimated variance is comprised of a variance term and a covariance term. We have found that increasing the reconstruction sampling rate can only reduce the variance term portion, and there is nothing to do with the covariance. We also found that the covariance term actually represents the extent to which indirect illumination samples are reused in the reconstruction process. The more the same indirect illumination sample is used by the more reconstruction samples, the more significant the covariance term is. Based on the analysis of variance, we propose an adaptive generation of indirect illumination sampling to reduce the covariance term. We applied this adaptive method to the indirect light field reconstruction algorithm and the axis-aligned image spatial filtering algorithm, and significantly reduced the distortion in the rendering results. (3) Finally, aiming at the color reuse of the image space, we present a light-cone-based ray tracing technique for high-quality rendering of hair objects. By aggregating all the light in one pixel into a light cone, we can actually reuse the calculated results for each sample within this cone to reduce the large amount of sample required for the fine geometry of the hair. So that not only the calculation cost of the sampling is reduced, but also the cost of the synthesis calculation required by the semi-transparent hair is reduced. The final result is a high-efficiency ray tracing algorithm that can generate the same quality rendering results as other methods, while significantly reducing the calculated time.
【學(xué)位授予單位】：浙江大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2016
【分類號(hào)】：TP391.41

【相似文獻(xiàn)】

相關(guān)期刊論文 前10條

1 袁樵,朱明華;計(jì)算機(jī)輔助前照燈設(shè)計(jì)中的光線跟蹤算法[J];照明工程學(xué)報(bào);2000年02期

2 陳家新,周緯杰;一種光線跟蹤的包容性檢測(cè)算法[J];計(jì)算機(jī)工程與應(yīng)用;2001年19期

3 崔智,張良震,朱淼良;基于光線跟蹤的數(shù)字影像重建技術(shù)[J];小型微型計(jì)算機(jī)系統(tǒng);2001年10期

4 王志敏;可見面光線跟蹤的區(qū)間分割加速算法[J];培訓(xùn)與研究(湖北教育學(xué)院學(xué)報(bào));2001年02期

5 陳家新,周緯杰;動(dòng)態(tài)光線跟蹤算法與實(shí)現(xiàn)[J];系統(tǒng)仿真學(xué)報(bào);2001年S2期

6 曹瑩,顧耀林,王駿;基于體單元的光線跟蹤算法[J];江南大學(xué)學(xué)報(bào);2002年04期

7 古春生,蔡勇;一種基于光線相關(guān)性的快速光線跟蹤算法[J];計(jì)算機(jī)與現(xiàn)代化;2003年06期

8 趙爽;李學(xué)軍;;復(fù)雜場(chǎng)景的快速光線跟蹤算法[J];計(jì)算機(jī)工程;2006年01期

9 劉文杰;于建娜;白紅進(jìn);;光線跟蹤算法在高質(zhì)量三維分子模型設(shè)計(jì)中的應(yīng)用[J];塔里木大學(xué)學(xué)報(bào);2006年02期

10 黃沛杰;王文成;楊剛;吳恩華;;基于中介面加快光線跟蹤計(jì)算[J];計(jì)算機(jī)學(xué)報(bào);2007年02期

相關(guān)會(huì)議論文 前4條

1 劉剛;梁曉庚;;基于SIMD硬件指令加速的并行光線跟蹤算法[A];第十屆中國(guó)科協(xié)年會(huì)論文集（一）[C];2008年

2 勞彩蓮;李保國(guó);郭焱;;基于光線跟蹤技術(shù)的植物冠層內(nèi)太陽(yáng)輻射光空間分布模擬[A];中國(guó)數(shù)字農(nóng)業(yè)與農(nóng)村信息化學(xué)術(shù)研究研討會(huì)論文集[C];2005年

3 王曉華;張?zhí)镂?;流體動(dòng)畫方法綜述[A];2003年全國(guó)系統(tǒng)仿真學(xué)術(shù)年會(huì)論文集[C];2003年

4 申亞斌;陳磊;冼樹章;;基于WebGIS的城市污染源地理信息發(fā)布方法探索[A];第三屆長(zhǎng)三角科技論壇（測(cè)繪分論壇）暨'2006江蘇省測(cè)繪學(xué)術(shù)年會(huì)論文集[C];2006年

相關(guān)重要報(bào)紙文章 前1條

1 彭;造霧機(jī)與電腦制圖[N];電腦商報(bào);2008年

相關(guān)博士學(xué)位論文 前6條

1 秦昊;光線跟蹤繪制中的光路重用技術(shù)研究[D];浙江大學(xué);2016年

2 柴國(guó)貝;激光雷達(dá)成像特征分析及應(yīng)用研究[D];西安電子科技大學(xué);2016年

3 蔡鵬;基于光線跟蹤與光子映射的點(diǎn)云數(shù)據(jù)繪制[D];北京工業(yè)大學(xué);2013年

4 周鵬;基于光線跟蹤的真實(shí)感全局光照問題研究[D];山東大學(xué);2012年

5 殷明強(qiáng);大規(guī)模裝配場(chǎng)景仿真關(guān)鍵技術(shù)研究[D];華中科技大學(xué);2013年

6 權(quán)勇;基于點(diǎn)表示的幾何體的造型與繪制研究[D];吉林大學(xué);2009年

相關(guān)碩士學(xué)位論文 前10條

1 雍鑫;基于光線跟蹤的眩光效果仿真研究[D];西安電子科技大學(xué);2015年

2 田利敏;基于光線跟蹤的高真實(shí)感紅外場(chǎng)景生成[D];西安電子科技大學(xué);2014年

3 甘龍飛;高逼真度虛擬森林環(huán)境下光線跟蹤加速模擬及應(yīng)用研究[D];福州大學(xué);2013年

4 郭小凱;光線跟蹤及其加速算法的研究[D];西安電子科技大學(xué);2008年

5 張璐;真實(shí)感虛擬場(chǎng)景中光線跟蹤算法的應(yīng)用與改進(jìn)[D];電子科技大學(xué);2008年

6 文建明;光線跟蹤及其反走樣的研究[D];西安電子科技大學(xué);2005年

7 甘筱銳;光線跟蹤繪制系統(tǒng)中的若干優(yōu)化技術(shù)[D];浙江大學(xué);2008年

8 李勇;光線跟蹤加速算法在異構(gòu)多核平臺(tái)上的設(shè)計(jì)與實(shí)現(xiàn)[D];南京郵電大學(xué);2011年

9 秦亞軍;光線跟蹤加速技術(shù)的研究與應(yīng)用[D];合肥工業(yè)大學(xué);2014年

10 王剛;基于光線跟蹤的動(dòng)畫場(chǎng)景空間加速結(jié)構(gòu)的研究[D];天津大學(xué);2008年

，

本文編號(hào)：2478776