In this paper, we suggest the enhanced compression scheme using the hybrid motion-estimation in sub-image array (SIA) transformed from elemental image array (EIA) in three-dimensional integral imaging. In the proposed method, firstly, a macroblock in the reference sub-image (SI) is matched in the local SI applying to MSE (Motion Square Estimation) by three step search (TSS) to search the coordinates of current macro block. The second step is to search the most matched area in SIs and the coordinate of macro block for full searching, and finally, the start point for searching in the local SI is altered by the former coordinate. Accordingly, the computed motion estimation from the block-matching with TSS and the full searching is presented as MV and the object in the reference SI is shifted to the object position of each current SIs to compensate their MV based on the motion estimation. The computation time for block-matching by the TSS to search approximate current macro block range in the first step and the full searching to acquire the exact current macro block range in the second step is decreased. In addition, the video compression such as MPEG-4 is applied to encode the data of the consecutive frames. Some experiments are carried out and compression efficiency of the proposed scheme has been improved 676.30%, 357.19% and 3.37% on the condition of 30[dB] approximately, compared with the JPEG compression, EIA compression and Full searching method. The computation time is also improved 196.97% compared with the full search scheme for motion estimation and compensation.
In this paper, we address a highly enhanced compression scheme in the condition of multiple objects in Integral
Imaging (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.
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