A Novel Image Fusion Scheme for FTV View Synthesis Based on Layered Depth Scene Representation & Scale Periodic Transform This paper presents a novel image fusion scheme for view synthesis based on a layered depth profile of the scene and scale periodic transform. To create a layered depth profile of the scene, we utilize the unique properties of scale transform considering the problem of depth map computation from reference images as a certain shiftvariant problem. The problem of depth computation is solved without deterministic stereo correspondences or rather than representing image signals in terms of shifts. Instead, we pose the problem of image signals being representable as scale periodic function, and compute appropriate depth estimates determining the scalings of a basis function. The rendering process is formulated as a novel image fusion in which the textures of all probable matching points are adaptively determined, leveraging implicitly the geometric information. The results demonstrate superiority of the proposed approach in suppressing geometric, blurring or flicker artifacts in rendered widebaseline virtual videos.

An Improved Depth Map Estimation Algorithm For View Synthesis and Multiview Video Coding In this paper, an improved algorithm to generate a smooth and accurate depth map for view synthesis and multiview video coding is developed. For each block in the target view, the algorithm first uses epipolar geometry to find its matched block in the reference view, from which an initial depth is obtained using the triangulation method and depth projection. 3D warping is then applied to refine the depth. In addition, a structural similarity and maximum likelihoodbased approach is developed to fuse the depth estimations from multiple references. Finally, the depth map is smoothed via segmentation and plane fitting. Compared to existing 3D warpingbased depth estimation, the proposed algorithm can achieve up to 4 dB improvement in view synthesis, while requires much fewer bits to encode the depth map. Experimental results in multiview video coding show that the proposed method can outperform the H.264 JMVC software by more than 1 dB.