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譯文摘錄：

基于集群機(jī)的并行繪制是提高圖形系統(tǒng)性能和分辨率的有效方法，圖像深度合成是sort-last并行繪制系統(tǒng)的關(guān)鍵步驟。本文提出了一套sort-last并行繪制系統(tǒng)中的圖像深度融合策略，該策略針對(duì)圖像深度數(shù)據(jù)的特點(diǎn)，提出了一個(gè)基于模板的深度信息LZW無(wú)損壓縮方法和圖像深度信息插值方法；針對(duì)圖像顏色數(shù)據(jù)的特點(diǎn)，給出了一個(gè)基于Jpeg的圖像顏色信息有損壓縮方法；針對(duì)圖像深度合成步驟，給出了一個(gè)基于透明度的融合方法。實(shí)驗(yàn)結(jié)果表明，該策略應(yīng)用于sort-last并行繪制系統(tǒng)中，優(yōu)于其它基于壓縮的圖像合成策略。

The cluster computer based parallel rendering is an effective method to improve graphics system performance and resolution, the image depth fusion is the key step of sort-last parallel rendering system. This paper puts forward a set of strategies of image depth fusion in sort-last parallel rendering system. Regarding this feature of image depth data, this strategy puts forward template based depth information LZW non-destructive compression method and image depth information interpolation method; regarding the feature of image color data, it puts forward Jpeg based image color information destructive compression method; regarding the image depth synthesis step, it gives a transparence based fusion method. The experimental result shows that this strategy is better than other compression based image synthesis strategies if it is used in sort-last parallel rendering system.

在虛擬現(xiàn)實(shí)技術(shù)的研究領(lǐng)域，高性能和高分辨率場(chǎng)景繪制的傳統(tǒng)方法是使用大型的專(zhuān)業(yè)圖形處理機(jī)，如SGI圖形機(jī)等，而隨著并行繪制概念的引入，繪制系統(tǒng)有了長(zhǎng)足的發(fā)展?；赑C集群的并行繪制系統(tǒng)的研究已經(jīng)成為構(gòu)建高性能、高精度要求的圖形系統(tǒng)的關(guān)鍵方法。1994年Molnar等人根據(jù)并行任務(wù)劃分的階段與典型圖形繪制流程的關(guān)系，將并行繪制系統(tǒng)劃分為三種類(lèi)型：sort-first，sort-middle，sort-last[1]。sort-first系統(tǒng)按照屏幕空間進(jìn)行任務(wù)劃分，但是圖元在屏幕上的分布不均勻及圖元復(fù)雜程序的差異容易導(dǎo)致系統(tǒng)負(fù)載不平衡；sort-middle一般適用于硬件實(shí)現(xiàn)；而sort-last并行繪制系統(tǒng)，不對(duì)圖像空間進(jìn)行劃分，各繪制處理器互相獨(dú)立操作，直到光柵化階段的最后才會(huì)重新分布像素。

In the research field of virtual reality technology, the traditional method of high performance and high resolution scene rendering is to use large scale professional graphics processors, e.g., SGI graphics processor, while with the introduction of parallel rendering concept, the rendering system has made rapid development. The research on PC cluster based parallel rendering system has become the key method constructing graphics system of high performance and high precision requirements. In 1994, Molnar and others divided the parallel rendering system into three types according to the relationship between the stages of parallel task division and typical graphics rendering flow: Sort-first, sort-middle and sort-last. Tasks of sort-first system are divided according to screen space, however, the uneven distribution of primitives on screen and difference of complex procedures of primitives easily leads to the imbalance of system load; sort-middle is usually applicable to hardware realization; while sort-last parallel rendering system does not divide graphics space, each rendering processor is independent mutually and redistribute pixels till the end of rasterization stage.

sort-last并行繪制系統(tǒng)因場(chǎng)景數(shù)據(jù)的不均勻分布引起的負(fù)載不平衡較小，但是卻增加了圖像融合的處理步驟，圖像的傳輸和融合是sort-last并行繪制系統(tǒng)的主要開(kāi)銷(xiāo)和瓶頸，因此如何縮短圖像數(shù)據(jù)的傳輸時(shí)間，優(yōu)化圖像的融合結(jié)果成為sort-last并行繪制系統(tǒng)的重要問(wèn)題。

Sort-last parallel rendering system causes little unbalanced load due to the uneven distribution of scene data, while increases the processing steps of image fusion. The transmission and fusion of image is the main overhead and bottleneck of sort-last parallel rendering system, so how to shorten the transmission time of image data and optimize the fusion result of image has become an important issue of sort-last parallel rendering system.

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