首页> 外文会议>Conference on optics and photonics for information processing >Compression scheme by use of object-segmented sub-image array transformed from computational elemental image array based on multiple objects in 3D integral imaging
【24h】

Compression scheme by use of object-segmented sub-image array transformed from computational elemental image array based on multiple objects in 3D integral imaging

机译:通过使用基于三维积分成像中的多个对象从计算元素图像阵列中转换的对象分段的子图像阵列进行压缩方案

获取原文

摘要

In this paper, we address a highly enhanced compression scheme in the condition of multiple objects in IntegralImaging (InIm) by use of sub-images (SIs) to segment each object and to remove the Motion Vector (MV) of residual image array transformed from Sub-Image Array (SIA). In the pick-up process, SIA is generated from EIA after the perspectives passing through virtual pinhole array is recorded as Elemental Image Array (EIA). The similarity enhancement among SIs expects compression efficiency to improve, but the compression efficiency of the EIA in the picked-up condition of multiple objects does not correspond to that of the picked-up condition of a simplified object. In the proposed scheme, the depth of objects is computed by two adaptive SIs located at horizontal left and right side from the reference SI positioned to the center of the SIA. A depth map image generated from two adaptive the SIs and a reference SI is applied to segment each object considering to the distance between those. Therefore, an adaptive objectsegmented SI is obtained and, which is motion-estimated from the original SIA based on MSE to generate the motioncompensated object-segmented SIA and which SIAs from each segmented object are finally combined as the motioncompensated SIA, and which based on multiple objects is transformed to residual SIA to minimize the spatial redundancy and which SIA is compressed by MPEG-4. The proposed algorithm shows the enhanced compression efficiency than that of the baseline JPEG and the conventional EIA compression scheme.© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
机译:在本文中,我们通过使用子图像(SIS)来划分每个对象并删除变换的残余图像阵列的动作向量(MV)的多个对象中的多个对象条件的高度增强的压缩方案子图像阵列(SIA)。在接送过程中,在通过虚拟针孔阵列的视角被记录为元素图像阵列(EIA)之后,SIA是从EIA生成的。 SIS之间的相似性增强期望压缩效率来改进,但是在多个对象的拾取条件下的EIA的压缩效率不对应于简化对象的拾取条件的压缩效率。在所提出的方案中,物体深度由位于水平左侧和右侧的两个自适应SI从位于SIA的中心的参考SI计算。从两个自适应的SIS和参考SI生成的深度映射图像被应用于将每个对象段考虑到那些之间的距离。因此,基于MSE获得自适应对象SID的SI,并且基于MSE从原始SIA运动估计,以生成运动代码化对象分段SIA,并且从每个分段对象的SIAS最终组合为运动代样SIA,并且基于多个对象被转换为残差SIA,以最小化空间冗余,并且通过MPEG-4压缩SIA。所提出的算法显示了增强的压缩效率,而不是基线JPEG和传统的EIA压缩方案。©(2012)照片光学仪表工程师(SPIE)的版权协会。仅供个人使用的摘要下载。

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