首页> 外文期刊>IEEE Transactions on Image Processing >Planelets—A Piecewise Linear Fractional Model for Preserving Scene Geometry in Intra-Coding of Indoor Depth Images
【24h】

Planelets—A Piecewise Linear Fractional Model for Preserving Scene Geometry in Intra-Coding of Indoor Depth Images

机译:小平面—在室内深度图像的帧内编码中保留场景几何的分段线性分数模型

获取原文
获取原文并翻译 | 示例

摘要

Geometrical wavelets have already proved their strength in approximation, compression, and denoising of piecewise constant and piecewise linear images. In this paper, we extend this family by introducing planelets toward an effective representation of indoor depth images. It uses a linear fractional model to capture non-linearity of depth values in the planar regions of the output images of Kinect-like sensors. A block-based compression framework based on planelet approximation is then presented, which uses quadtree decomposition along with spatial predictions as an effective intra-coding scheme. Compared with both classical geometric wavelets and some state-of-the-art image coding algorithms, our method provides desirable quality by explicitly representing edges and planar patches.
机译:几何小波已经证明了其在分段恒定和分段线性图像的逼近,压缩和去噪方面的优势。在本文中,我们通过引入小平面朝向室内深度图像的有效表示来扩展该家族。它使用线性分数模型来捕获类似Kinect的传感器的输出图像的平面区域中深度值的非线性。然后提出了一种基于平面近似的基于块的压缩框架,该框架使用四叉树分解以及空间预测作为有效的帧内编码方案。与经典几何小波和一些最新的图像编码算法相比,我们的方法通过显式表示边缘和平面斑块提供了令人满意的质量。

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