首页> 外文期刊>IEEE Transactions on Circuits and Systems for Video Technology >Object Shape Approximation and Contour Adaptive Depth Image Coding for Virtual View Synthesis
【24h】

Object Shape Approximation and Contour Adaptive Depth Image Coding for Virtual View Synthesis

机译:用于虚拟视图合成的目标形状近似和轮廓自适应深度图像编码

获取原文
获取原文并翻译 | 示例

摘要

A depth image provides partial geometric information of a 3D scene, namely the shapes of physical objects as observed from a particular viewpoint. This information is important when synthesizing images of different virtual camera viewpoints via depth-image-based rendering (DIBR). It has been shown that depth images can be efficiently coded using contour-adaptive codecs that preserve edge sharpness, resulting in visually pleasing DIBR-synthesized images. However, contours are typically losslessly coded as side information, which is expensive if the object shapes are complex. In this paper, we pursue a new paradigm in depth image coding for color-plus-depth representation of a 3D scene: in a pre-processing step, we pro-actively simplify object shapes in a depth and color image pair to reduce depth coding cost, at a penalty of a slight increase in synthesized view distortion. Specifically, we first mathematically derive a distortion upper-bound proxy for 3DSwIM—a quality metric tailored for DIBR-synthesized images. This proxy reduces inter-dependency among pixel rows in a block to ease optimization. We then approximate object contours via a dynamic programming algorithm to optimally tradeoff coding the cost of contours using arithmetic edge coding with our proposed view synthesis distortion proxy. We modify the depth and color images according to the approximated object contours in an inter-view consistent manner. These are then coded, respectively, using a contour-adaptive image codec based on graph Fourier transform for edge preservation and High Efficiency Video Coding (HEVC) intra. Experimental results show that by maintaining sharp but simplified object contours during contour-adaptive coding, for the same visual quality of DIBR-synthesized virtual views, our proposal can reduce depth image coding rate by up to 22% in 3DSwIM and 42% in peak signal-to-noise ratio compared with alternative coding strategies, such as HEVC intra.
机译:深度图像提供3D场景的部分几何信息,即从特定视点观察到的物理对象的形状。通过基于深度图像的渲染(DIBR)合成不同虚拟摄像机视点的图像时,此信息很重要。已经表明,可以使用保持边缘清晰度的轮廓自适应编解码器对深度图像进行有效编码,从而在视觉上令人愉悦的DIBR合成图像。然而,轮廓通常被无损地编码为辅助信息,如果物体形状复杂,这将是昂贵的。在本文中,我们追求用于3D场景的颜色加深度表示的深度图像编码的新范例:在预处理步骤中,我们主动简化深度和彩色图像对中的对象形状以减少深度编码成本,但综合视图失真会略有增加。具体来说,我们首先从数学上推导3DSwIM的失真上限代理,这是一种为DIBR合成的图像量身定制的质量指标。该代理减少了块中像素行之间的相互依赖性,以简化优化。然后,我们通过动态规划算法对目标轮廓进行近似,以利用算术边缘编码与我们提出的视图合成失真代理对轮廓的成本进行最佳权衡编码。我们按照视图间一致的方式根据近似的对象轮廓修改深度和彩色图像。然后分别使用基于图形傅立叶变换的轮廓自适应图像编解码器对它们进行编码,以进行边缘保留和内部高效视频编码(HEVC)。实验结果表明,通过在轮廓自适应编码过程中保持清晰但简化的对象轮廓,对于DIBR合成的虚拟视图的相同视觉质量,我们的建议可以将3DSwIM和42 中的深度图像编码率降低多达22%。与其他编码策略(例如HEVC内部)相比,峰值信噪比的百分比为%。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号