This paper presents the application of a depth estimation method for scenes acquired using a Synthetic Aperture Integral Imaging (SAII) technique. SAII is an autostereoscopic technique consisting of an array of cameras that acquires images from different perspectives. The depth estimation method combines a defocus and a correspondence measure. This approach obtains consistent results and shows noticeable improvement in the depth estimation as compared to a minimum variance minimisation strategy, also tested in our scenes. Further improvements are obtained for both methods when they are fed into a regularisation approach that takes into account the depth in the spatial neighbourhood of a pixel.
CITATION STYLE
Espinos-Morato, H., Latorre-Carmona, P., Martinez Sotoca, J., Pla, F., & Javidi, B. (2017). Combining defocus and photoconsistency for depth map estimation in 3D integral imaging. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10255 LNCS, pp. 114–121). Springer Verlag. https://doi.org/10.1007/978-3-319-58838-4_13
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