Lourenco, RuiRivero-Castillo, DanielThomaz, Lucas A.Assuncao, Pedro A. A.Tavora, Luis M. N.Faria, Sergio M. M. de2025-07-162025-07-162020-11R. Lourenco, D. Rivero-Castillo, L. A. Thomaz, P. A. A. Assuncao, L. M. N. Tavora and S. M. M. de Faria, "4D Light Field Disparity Map estimation using Krawtchouk Polynomials," 2020 Tenth International Conference on Image Processing Theory, Tools and Applications (IPTA), Paris, France, 2020, pp. 1-6, doi: https://doi.org/10.1109/IPTA50016.2020.9286454.978-1-7281-8751-8978-1-7281-8750-12154-5111http://hdl.handle.net/10400.8/13679EISBN - 978-1-7281-8750-1Article number - 9286454; Conference date - 9 November 2020 - 12 November 2020; Conference code - 165865This work presents an improved method to estimate disparity maps obtained from light field cameras using a novel edge detection algorithm based on Krawtchouk polynomials. The proposed method takes advantage of these polynomials to determine gradient information and find the edges based on automatically estimated weak and strong thresholds. The calculated edges in the gray scale epipolar plane image representation of a light field are then used to improve the accuracy of object boundaries in the the disparity map. The proposed method achieves better results when compared to other edge detection algorithms, both in terms of objective and subjective quality, specifically by reducing the mean squared error and the artifacts in the object boundaries. Furthermore, on average, the proposed method outperforms the state-of-the-art depth estimation algorithms, in terms of the objective quality of the final disparity map, namely for the commonly used HCI dataset.engLight FieldDisparityDepthEdge DetectionKrawtchouk PolynomialsStructure Tensorconference paper10.1109/ipta50016.2020.92864542154-512X