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Wavelet based stereo images reconstruction using depth images

机译:使用深度图像的基于小波的立体图像重建

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It is believed by many that three-dimensional (3D) television will be the next logical development toward a more natural and vivid home entertaiment experience. While classical 3D approach requires the transmission of two video streams, one for each view, 3D TV systems based on depth image rendering (DIBR) require a single stream of monoscopic images and a second stream of associated images usually termed depth images or depth maps, that contain per-pixel depth information. Depth map is a two-dimensional function that contains information about distance from camera to a certain point of the object as a function of the image coordinates. By using this depth information and the original image it is possible to reconstruct a virtual image of a nearby viewpoint by projecting the pixels of available image to their locations in 3D space and finding their position in the desired view plane. One of the most significant advantages of the DIBR is that depth maps can be coded more efficiently than two streams corresponding to left and right view of the scene, thereby reducing the bandwidth required for transmission, which makes it possible to reuse existing transmission channels for the transmission of 3D TV. This technique can also be applied for other 3D technologies such as multimedia systems. In this paper we propose an advanced wavelet domain scheme for the reconstruction of stereoscopic images, which solves some of the shortcommings of the existing methods discussed above. We perform the wavelet transform of both the luminance and depth images in order to obtain significant geometric features, which enable more sensible reconstruction of the virtual view. Motion estimation employed in our approach uses Markov random field smoothness prior for regularization of the estimated motion field. The evaluation of the proposed reconstruction method is done on two video sequences which are typically used for comparison of stereo reconstruction algorithms. The results demonstrate advantages of the proposed approach with respect to the state-of-the-art methods, in terms of both objective and subjective performance measures.
机译:许多人相信,三维(3D)电视将是朝着更自然,生动的家庭娱乐体验发展的下一个逻辑发展。传统的3D方法需要传输两个视频流,每个视图传输一个视频流,而基于深度图像渲染(DIBR)的3D电视系统则需要单个单视场图像流和第二个相关图像流,通常称为深度图像或深度图,包含每个像素的深度信息。深度图是一个二维函数,其中包含有关从相机到对象某个点的距离的信息,该信息是图像坐标的函数。通过使用此深度信息和原始图像,可以通过将可用图像的像素投影到3D空间中的像素位置并在所需的视平面中找到它们的位置,来重建附近视点的虚拟图像。 DIBR的最重要优点之一是,与对应于场景左右视图的两个流相比,深度图的编码效率更高,从而减少了传输所需的带宽,这使得可以将现有传输通道重用于传输3D电视。该技术还可以应用于诸如多媒体系统的其他3D技术。在本文中,我们提出了一种用于重构立体图像的高级小波域方案,该方案解决了上述现有方法的一些缺点。为了获得重要的几何特征,我们对亮度和深度图像都进行了小波变换,从而可以更合理地重建虚拟视图。在我们的方法中采用的运动估计是先使用马尔可夫随机场平滑度对估计的运动场进行正则化。所提出的重建方法的评估是在两个视频序列上完成的,这些视频序列通常用于比较立体声重建算法。结果表明,就客观和主观绩效衡量而言,该方法相对于最新方法的优势。

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