北京生物醫(yī)學(xué)工程

基于可伸縮窗視差生成的開放手術(shù)視頻虛擬視點合成算法

Virtual view synthesis algorithm for operation video based on disparity generated with adaptive window

作者：賈博奇張夢詩梁楠武博張楠

單位：首都醫(yī)科大學(xué)生物醫(yī)學(xué)工程學(xué)院（北京 100069）

關(guān)鍵詞：視差;手術(shù)視頻;虛擬視點合成;可伸縮窗;基于深度圖繪制

分類號：R318.04

出版年·卷·期（頁碼）：2018·37·6（603-610）

摘要：

目的本文為了提高開放手術(shù)視頻的視差圖質(zhì)量, 減少虛擬視點中空洞, 提升虛擬視點主觀質(zhì)量, 提出基于可伸縮窗視差生成的虛擬視點合成算法, 為醫(yī)學(xué)專家和醫(yī)學(xué)生獲得身臨其境的手術(shù)示教和手術(shù)指導(dǎo)提供了可能。方法根據(jù)場景內(nèi)容特點確定匹配窗口大小并進行立體匹配, 生成手術(shù)場景視差信息;基于深度繪制原理, 針對手術(shù)場景的特性填充空洞, 獲得手術(shù)場景虛擬視點圖像, 并對虛擬視點的主觀質(zhì)量進行評估。結(jié)果與固定窗方法相比較, 本文算法生成的虛擬視點圖像中術(shù)野內(nèi)物體邊緣較光滑, 存在較少偽影。結(jié)論本文算法生成的手術(shù)虛擬視點視頻取得了較高的主觀質(zhì)量, 為觀看者提供了更好的觀看體驗。

Objective To improve the quality of disparity maps in open operation videos and to reduce holes in virtual views, the virtual view synthesis algorithm based on disparity generated with adaptive window is proposed. Methods According to the characteristics of the scene content, the size of the matching window is determined and stereo matching is performed to generate disparity information of the surgical scene. Based on depth image based render ( DIBR) , the holes are filled with the characteristics of the surgical scene, and then the subjective quality of the obtained virtual view is evaluated. Results Compared with the fix window method, the edges of the objects in the operative field in the virtual view generated by this algorithm are smooth and have fewer artifacts. Conclusions This algorithm can achieve a high subjective quality and offer a better viewing experience.

參考文獻：

[1]呂源治, 王世剛, 任廣旭, 等.二維多視點圖像陣列采集及虛擬視點合成算法[J].哈爾濱工程大學(xué)學(xué)報, 2013, 34 (6) :763-767, 795.Lyu YZ, Wang SG, Ren GX, et al, Two dimensional multiview image array pickup and virtual viewpoint image synthesis algorithm[J]. Journal of Harbin Engineering University, 2013, 34 (6) :763-767, 795.

[2] Xu X, Po LM, Ng KH, et al. Depth map misalignment correction and dilation for DIBR view synthesis[J]. Signal Processing:Image Communication, 2013, 28 (9) :1023-1045.

[3] Sharma M, Chaudhury S, Lall B. A novel hybrid kinect-varietybased high-quality multiview rendering scheme for glass-free 3D displays[J]. IEEE Transactions on Circuits and Systems for Video Technology, 2017, 27 (10) :2098-2117.

[4]何貝, 王貴錦, 林行剛.結(jié)合Kinect深度圖的快速視頻摳圖算法[J].清華大學(xué)學(xué)報 (自然科學(xué)版) , 2012, 52 (4) :561-565, 570.He B, Wang GJ, Lin HG. Quick matting for videos based on depth images of the Kinect[J]. Journal of Tsinghua University (Science and Technology) , 2012, 52 (4) :561-565, 570.

[5] Han CC, Hsiao HF. Depth estimation and video synthesis for 2D to 3D video conversion[J]. Journal of Signal Process Systems, 2014, 76:33-46.

[6] Gu Z, Su X, Liu Y, et al. Local stereo matching with adaptive support-weight, rank transform and disparity calibration[J].Pattern Recognition Letters, 2008, 29 (9) :1230-1235.

[7] Kanade T, Okutomi M. A stereo matching algorithm with an adaptive window:theory and experiment[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1994, 16 (9) :920-932.

[8]張來剛, 魏仲慧, 何昕, 等.面向低紋理圖像的快速立體匹配[J].液晶與顯示, 2013, 28 (3) :450-458.Zhang LG, Wei ZH, He X, et al. New stereo matching method based edge extraction[J]. Chinese Journal of Liquid Crystals and Displays, 2013, 28 (3) :450-458.

[9]劉杰, 張建勛, 代煜, 等.基于跨尺度引導(dǎo)圖像濾波的稠密立體匹配[J].光學(xué)學(xué)報, 2018, 38 (1) :0115004.Liu J, Zhang JX, Dai Y, et al. Dense Stereo Matching Based on Cross-Scale Guided Image Filtering[J]. Acta Optica Sinica, 2018, 38 (1) :0115004.

[10]汪輝, 陳芬, 焦任直, 等.基于空間加權(quán)的虛擬視點繪制算法[J].計算機工程與應(yīng)用, 2016, 52 (8) :174-179.Wang H, Chen F, Jiao RZ, et al. Virtual view rendering algorithm based on spatial weighting[J]. Computer Engineering and Applications, 2016, 52 (8) :174-179.

[11] Criminisi A, Pérez P, Toyama K. Region filling and object removal by exemplar-based image inpainting[J]. IEEE Transactions on Image Processing, 2004, 13 (9) :1200-1212.

[12] Ahn I, Kim C. A novel depth-based virtual view synthesis method for free viewpoint video[J]. IEEE Transactions on Broadcasting, 2013, 59 (4) :614-626.

[13] Lai Y, Lan X, Liu Y, et al. An efficient depth image-based rendering with depth reliability maps for view synthesis[J].Journal of Visual Communication and Image Representation, 2016, 41:176-184.

[14] Schmeing M, Jiang X. Faithful Disocclusion Filling in Depth Image Based Rendering Using Superpixel-Based Inpainting[J].IEEE Transactions on Multimedia, 2015, 17 (12) :2160-2173.

[15]李超, 沈建新, 梁春.裸眼3D技術(shù)在顯微手術(shù)中的研究與應(yīng)用[J].計算機技術(shù)與發(fā)展, 2015, 25 (7) :170-173.Li C, Shen JX, Liang C. Research and application of naked-eye3D technology in microsurgery[J]. Computer Technology and Development, 2015, 25 (7) :170-173.

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