Abstract
This paper presents a neural network based method to estimate a high resolution image from a sequence of low resolution image frames. In this method, a multiple of layered feed-forward neural networks is specially designed to learn an optimal mapping from a multiple of low resolution image frames to a high resolution image through training. Simulation results demonstrate that the proposed neural networks can successfully learn the mapping in the presented examples and show a good potential in solving image resolution enhancement problem, as it can adapt itself to the various changeable conditions. Furthermore, due to the inherent parallel computing structure of neural network, this method can be applied for real-time application, alleviating the computational bottlenecks associated with other methods and providing a more powerful tool for image resolution enhancement.
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Zhang, S., Salari, E. (2011). A Neural Network Method for Image Resolution Enhancement from a Multiple of Image Frames. In: Liu, D., Zhang, H., Polycarpou, M., Alippi, C., He, H. (eds) Advances in Neural Networks – ISNN 2011. ISNN 2011. Lecture Notes in Computer Science, vol 6677. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21111-9_22
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DOI: https://doi.org/10.1007/978-3-642-21111-9_22
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-21110-2
Online ISBN: 978-3-642-21111-9
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