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Browsing by Author "Rivero-Castillo, Daniel"

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  • 4D Light Field Disparity Map estimation using Krawtchouk Polynomials
    Publication . Lourenco, Rui; Rivero-Castillo, Daniel; Thomaz, Lucas A.; Assuncao, Pedro A. A.; Tavora, Luis M. N.; Faria, Sergio M. M. de
    This 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.
    2020-11Conference paper Open access Show more
  • Edge detection based on Krawtchouk polynomials
    Publication . Rivero-Castillo, Daniel; Pijeira, Héctor; Assunção, Pedro
    Abstract Discrete orthogonal polynomials are useful tools in digital image processing to extract visual object contours in different application contexts. This paper proposes an alternative method that extends beyond classic first-order differential operators, by using the properties of Krawtchouk orthogonal polynomials to achieve a first order differential operator. Therefore, smoothing of the image with a 2-D Gaussian filter is not necessary to regularize the ill-posed nature of differentiation. Experimentally, we provide simulation results which show that the proposed method achieves good performance in comparison with commonly used algorithms.
    2015-08Journal article Open access Show more