The quality assessment of Depth-Image-Based-Rendering (DIBR) synthesized views is very challenging owing to the new types of distortions, thus the traditional 2D quality metrics may fail to evaluate the quality of the synthesized views. In this paper, we propose a full-reference metric to assess the quality of DIBR synthesized views. Firstly, we notice that the object shift in the synthesized view is approximately linear, an affine transformation is used to warp the pixel in the reference image to the corresponding position in the distorted image. Besides, since the synthesis distortions mainly happen in the dis-occluded areas, a dis-occlusion mask obtained from the depth map in the original viewpoint is used to weight the final distortions between the synthesized image and the reference image. The experimental results on IRCCyN/IVC DIBR image database show that the proposed weighted PSNR (PSNR') outperforms the state-of-the-art DIBR synthesized view dedicated metrics: 3DSwIM, VSQA, MP-PSNR, MW-PSNR and earns a gain of 36.85% (in terms of PLCC) over PSNR. The weighted SSIM (SSIM') earns a gain of 13.33% (in terms of PLCC) compared to SSIM.
This work focuses on estimating an accurate 3D transformation in real time, which is used to register images acquired from different viewpoints. The main challenges are significant image appearance differences, which originate from lateral displacements and parallax, inconsistencies in our 3D model and achieving real-time execution. To this end, we propose a featurebased method using a single synthesized view, which can cope with significant image appearance differences. The 3D transformation is estimated using an EPnP refinement to minimize the influence of inconsistencies in the 3D model. We demonstrate that the proposed method achieves over 95% transformation accuracy for lateral displacements up to 350 cm, while still achieving 85% accuracy at displacements of 530 cm. Additionally, with a running time of 100 milliseconds, we achieve real-time execution as a result of efficiency optimizations and GPU implementations of time-critical components.