Abstract
Face hallucination, which refers to the restoration of single or multiple low-resolution face images into clear high-resolution one, is a challenging research issue. Most existing methods use local or global patches for image representation and achieve good performance. However, they ignore that the local patch limits the area of the receptive field and the priori information used in reconstruction is limited. And the global patch expands the receptive field but introduces irrelevant information to degrade the reconstruction performance. In order to improve the performance of reconstruction, we propose a nonlinear contextual face hallucination method. First, contextual information can effectively improve the receptive field area to make full use of priori information. Then, the nonlinear model can make the proposed model more suitable for practical application and make the correlation of data in kernel space more compact. Finally, combining contextual and residual learning can improve the stability of the solution of the super-resolution model and the accuracy of reconstruction performance. The experimental results show that the proposed face hallucination method has superior performance than the state-of-the-art method.
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Acknowledgement
This work is supported by the National Natural Science Foundation of China (61502354, 61501413, 61671332, 41501505), the Natural Science Foundation of Hubei Province of China (2015CFB451, 2014CFA130, 2012FFA099, 2012FFA134, 2013CF125), the Central Government Guided Local Science and Technology Development Projects (2018ZYYD059), Provincial Teaching Research Project of Hubei Province Higher Education (2017324), Wuhan Institute of Technology Key Teaching Project (Z2017009), Scientific Research Foundation of Wuhan Institute of Technology (K201713).
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Zeng, K., Lu, T., Jiang, J., Wang, Z. (2019). Nonlinear Contextual Face Hallucination. In: Zhai, G., Zhou, J., An, P., Yang, X. (eds) Digital TV and Multimedia Communication. IFTC 2018. Communications in Computer and Information Science, vol 1009. Springer, Singapore. https://doi.org/10.1007/978-981-13-8138-6_21
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DOI: https://doi.org/10.1007/978-981-13-8138-6_21
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