本文選題：多視點圖像 + 深度圖像　； 參考：《上海師范大學(xué)》2017年碩士論文

【摘要】：與傳統(tǒng)的2D和3D電視相比,多視點能允許用戶在一定的范圍內(nèi)自由選擇視角,觀看其感興趣的內(nèi)容,因此可以給用戶帶來更震撼的視覺沖擊力、豐富的立體感和非比尋常的三維沉浸感。相比于當(dāng)前的高清視頻,多視點視頻的數(shù)據(jù)量會隨著視點數(shù)的增加呈線性增長,目前的存儲介質(zhì)和網(wǎng)絡(luò)帶寬顯然無法滿足多視點立體視頻的要求。而基于深度圖像的繪制(DIBR,Depth Image Based Rendering)技術(shù)是多視點視頻的關(guān)鍵技術(shù)之一,它有效的結(jié)合了紋理圖像和對應(yīng)的深度圖像的信息,使得任意新視點圖像中的各個像素點都可以通過3D圖像映射方程得到。該項技術(shù)憑借其節(jié)省數(shù)據(jù)空間和網(wǎng)絡(luò)帶寬、質(zhì)量高、繪制速度快的優(yōu)點而被公認為是下一代三維立體視頻的候選方案。然而,獲取高質(zhì)量的深度圖是十分具有挑戰(zhàn)的,它的準確度直接影響立體視頻的繪制質(zhì)量。針對上面的問題,本文的主要工作和成果如下:1.提出了一種基于Kinect的高準確度深度獲取的圖像增強算法,從Kinect獲取背景紋理圖,并采用形態(tài)學(xué)濾波與雙邊濾波相結(jié)合的方法填充空洞。采用三維高斯混合模型(3DGMM,3D Gauss mixture model)來分離深度圖像的前景和背景。針對空洞出現(xiàn)的區(qū)域做不同的處理。背景空洞采用對應(yīng)的背景值的填充,前景空洞采用顏色匹配和結(jié)構(gòu)相似性結(jié)合的算法填充,獲取到可靠的深度圖像。2.提出了一種改進的基于方向紋理的虛擬視點合成方法,將配準后的紋理圖和最終的深度圖經(jīng)三維映射后得到虛擬視點的紋理圖和深度圖,映射后的新視點圖像中的空洞存在的區(qū)域分為前景空洞和背景空洞,背景區(qū)域的空洞采用基于背景值的填充,前景區(qū)域空洞采用改進的基于方向紋理的虛擬視點合成的圖像修復(fù)技術(shù)進行修復(fù),得到較好虛擬視點圖像。3.提出了一種基于感興趣區(qū)域的多視點顏色校正算法并進行質(zhì)量評價。首先獲取多視點視頻的源圖像和目標圖像,然后提取目標圖像的感興趣區(qū)域的顯著性圖,對顯著圖和源圖像對應(yīng)區(qū)域進行匹配,最后對匹配后的圖像進行主客觀質(zhì)量評價。實驗結(jié)果表明,與傳統(tǒng)的三維高斯混合模型的算法相比,該算法的客觀質(zhì)量評價結(jié)果與主觀感知質(zhì)量有較好的一致性。
[Abstract]:Compared with traditional 2D and 3D TVs, multi-view allows users to freely select their views and view the content of their interest within a certain range, thus giving users a more shocking visual impact.Rich three-dimensional and unusual three-dimensional immersion.Compared with the current high-definition video, the amount of multi-view video data will increase linearly with the increase of the number of views. The current storage media and network bandwidth obviously can not meet the requirements of multi-view stereo video.The depth image rendering Image Based rendering is one of the key technologies of multi-view video, which effectively combines the texture image and the corresponding depth image information.Each pixel in any new view image can be obtained by 3D image mapping equation.Because of its advantages of saving data space and network bandwidth, high quality and high rendering speed, this technology is recognized as a candidate for the next generation 3D stereo video.However, obtaining high quality depth maps is a challenge, and its accuracy directly affects the quality of stereo video rendering.In view of the above questions, the main work and results of this paper are as follows: 1.An image enhancement algorithm with high accuracy and depth acquisition based on Kinect is proposed. The background texture image is obtained from Kinect, and the cavity is filled with morphological filtering and bilateral filtering.The 3D Gauss mixture model of 3D Gao Si is used to separate the foreground and background of depth image.Do different treatment for the area where the void occurs.The background cavity is filled with the corresponding background value, and the foreground cavity is filled with a combination of color matching and structural similarity to obtain a reliable depth image.An improved virtual viewpoint synthesis method based on directional texture is proposed. The texture map and depth map of virtual view are obtained by 3D mapping of the registered texture image and the final depth map.The voids in the mapped new view images can be divided into foreground voids and background voids, and the voids in the background regions are filled with background values.The voids in the foreground region are repaired by an improved image restoration technique based on directional texture-based virtual view synthesis, and a better virtual view image .3is obtained.A multi-view color correction algorithm based on region of interest is proposed and its quality is evaluated.Firstly, the source image and target image of multi-view video are obtained, then the salient map of the region of interest of the target image is extracted, and the corresponding regions of salient image and source image are matched. Finally, the subjective and objective quality evaluation of the matched image is carried out.The experimental results show that the objective quality evaluation results of this algorithm are in good agreement with the subjective perceived quality compared with the traditional three dimensional Gao Si hybrid model.
【學(xué)位授予單位】：上海師范大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TP391.41;TN948.6

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