Occlusion removal method of partially occluded 3D object using sub-image block matching in computational integral imaging

In this paper, we propose an occlusion removal method using sub-image block matching for improved recognition of partially occluded 3D objects in computational integral imaging (CII). When 3D plane images are reconstructed in CII, occlusion degrades the resolution of reconstructed images. To overcome this problem, we apply the sub-image transform to elemental image array (EIA) and these sub-images are employed using block matching method for depth estimation. Based on the estimated depth information, we remove the unknown occlusion. After completing the occlusion removal for all sub-images, we obtain the modified EIA without occlusion information through the inverse sub-image transform. Finally, the 3D plane images are reconstructed by using a computational integral imaging reconstruction method with the modified EIA. The proposed method can provide a substantial gain in terms of the visual quality of 3D reconstructed images. To show the usefulness of the proposed method we carry out some experiments and the results are presented.