【摘要】：半自動2D轉3D是解決當前3D影視內容匱乏的重要途徑�，F有方法大多借助局部鄰域進行深度插值,忽略了圖像的全局約束關系,因而難以準確恢復深度圖的對象邊界。針對該問題,提出鄰域擴展的最優(yōu)化深度插值方法。首先引入鄰域的鄰域,建立鄰域擴展的最優(yōu)化深度插值能量模型;其次在相似的像素點與其鄰域加權深度平均值的差異近似相等的假設條件下,將深度插值能量模型的最優(yōu)化問題轉換成一個稀疏線性方程組的求解問題。實驗結果表明,與當前流行的半自動2D轉3D方法相比,該方法估計的深度圖PSNR更高,同時增強了深度圖的對象邊界質量。
[Abstract]:Semi-automatic 2D to 3D is an important way to solve the shortage of 3D video content. Most of the existing methods use local neighborhood to carry out depth interpolation, ignoring the global constraint of the image, so it is difficult to accurately restore the object boundary of the depth map. To solve this problem, an optimal depth interpolation method based on neighborhood extension is proposed. Firstly, the neighborhood of the neighborhood is introduced to establish the optimal depth interpolation energy model of the neighborhood extension; secondly, under the assumption that the difference between the similar pixel points and the weighted depth mean of the neighborhood is approximately equal to that of the average value of the weighted depth of the neighborhood, the optimal depth interpolation energy model is established. The optimization problem of depth interpolation energy model is transformed into a sparse linear equation system. The experimental results show that compared with the popular semi-automatic 2D / 3D method, the proposed method can estimate the depth map with a higher PSNR and enhance the object boundary quality of the depth map.
【作者單位】： 南京理工大學泰州科技學院計算機科學與技術系;寧波工程學院電子與信息工程學院;
【基金】：國家自然科學基金資助項目(61170200) 浙江省自然科學基金資助項目(LY16F010014)
【分類號】：TP391.41
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本文編號：2247684