A method for image stitching is presented. The approach focuses on images with parallax (depth variation) to create panoramic views with high fidelity. The approach creates the stitching seam at a virtual depth to convert hard stitching problems to simple ones. The virtual depth is created by applying local distortions to the input images at the stitching seam so that the contents visually appear to be located at the same depth. The presented approach targets a wide variety of applications that require generating high (or super) resolution, wide-view images. These applications include tele-presence (or tele-reality) applications such as shopping, touring, conferencing, planning or architecting, learning, inspection, and surveillance. Our results show that the proposed approach provides promising results compared to commercial products that rely on stitching solutions.
In this contribution, an objective metric for quality evaluation of light field images is presented. The method is based on the exploitation of the depth information of a scene, that is captured with high accuracy by the light field imaging system. The depth map is estimated both from the original and impaired light field data. Then, a similarity measure is applied, and a mapping is performed to link the depth distortion with the perceived quality. Experimental test performed by comparing state-of-art metrics with the proposed one, demonstrate the effectiveness of the proposed metric.