Abstract
In this paper, we propose a novel approach to effectively compress the sub-images transformed from the picked-up elemental images in integral imaging, in which motion vectors of the object in each sub-image are fast and accurately estimated and compensated by combined use of MSE(mean square error)-based TSS(tree-step search) and FS(full search) schemes. This is, the possible object areas in each sub-image are searched by using the fast TSS algorithm in advance, then the these selected object areas are fully searched with the accurate FS algorithm. Furthermore, the sub-images in which all object's motion vectors are compensated, are transformed into the residual images by using the difference image method and finally compressed with the MPEG-4 algorithm. Experimental results reveal that the proposed method shows 214% improvement in the compression time per each image frame compared to that of the conventional method while keeping the same compression ratio with the conventional method. These successful results confirm the feasibility of the proposed method in the practical application.
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