Edge enhancement of depth based rendered images

M. S. Farid, M. Lucenteforte, Marco Grangetto
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引用次数: 16

Abstract

Depth image based rendering is a well-known technology for the generation of virtual views in between a limited set of views acquired by a cameras array. Intermediate views are rendered by warping image pixels based on their depth. Nonetheless, depth maps are usually imperfect as they need to be estimated through stereo matching algorithms; moreover, for representation and transmission requirements depth values are obviously quantized. Such depth representation errors translate into a warping error when generating intermediate views thus impacting on the rendered image quality. We observe that depth errors turn to be very critical when they affect the object contours since in such a case they cause significant structural distortion in the warped objects. This paper presents an algorithm to improve the visual quality of the synthesized views by enforcing the shape of the edges in presence of erroneous depth estimates. We show that it is possible to significantly improve the visual quality of the interpolated view by enforcing prior knowledge on the admissible deformations of edges under projective transformation. Both visual and objective results show that the proposed approach is very effective.
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基于深度渲染图像的边缘增强
基于深度图像的渲染是一种众所周知的技术,用于在相机阵列获取的有限视图之间生成虚拟视图。中间视图是通过根据深度扭曲图像像素来渲染的。尽管如此,深度图通常是不完美的,因为它们需要通过立体匹配算法来估计;此外,为了表示和传输的要求,深度值被明显量化。这种深度表示错误在生成中间视图时转化为扭曲错误,从而影响渲染图像质量。我们观察到,深度误差在影响物体轮廓时变得非常关键,因为在这种情况下,它们会在扭曲的物体中引起严重的结构扭曲。本文提出了一种在存在错误深度估计的情况下,通过强化边缘形状来提高合成视图视觉质量的算法。我们证明了在投影变换下,通过对边缘的可允许变形施加先验知识,可以显著提高插值视图的视觉质量。视觉和客观结果表明,该方法是非常有效的。
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