Abstract
Edge detection in image processing is a difficult but meaningful problem. In this paper, we propose a variational model with L 1-norm as the fidelity term based on the well-known Mumford-Shah functional. To solve it, we devise fast numerical algorithms through applying the binary label-set method. Numerical experiments on gray-scale images are given. By comparing with the famous Ambrosio-Tortorelli model with L 1-norm as the fidelity term, we demonstrate that our model and algorithms show advantages in efficiency and accuracy for impulse noise.
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Shi, Y., Guo, F., Su, X., Xu, J. (2014). Edge Detection in Presence of Impulse Noise. In: Tan, T., Ruan, Q., Wang, S., Ma, H., Huang, K. (eds) Advances in Image and Graphics Technologies. IGTA 2014. Communications in Computer and Information Science, vol 437. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45498-5_2
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DOI: https://doi.org/10.1007/978-3-662-45498-5_2
Publisher Name: Springer, Berlin, Heidelberg
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