Abstract
We propose a new convolutional network architecture called as UDLR Convolutional Network for improving the recently proposed Neural Adaptive Image DEnoiser (NAIDE). More specifically, we develop UDLR filters that meet the conditional independence constraint of NAIDE. By using the UDLR network, we could achieve a denoising result that significantly outperforms the state-of-the-art CNN-based methods on a standard benchmark dataset.
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Cha, S., Moon, T. (2019). UDLR Convolutional Network for Adaptive Image Denoiser. In: Kim, JH., Myung, H., Lee, SM. (eds) Robot Intelligence Technology and Applications. RiTA 2018. Communications in Computer and Information Science, vol 1015. Springer, Singapore. https://doi.org/10.1007/978-981-13-7780-8_5
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DOI: https://doi.org/10.1007/978-981-13-7780-8_5
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