Probabilistic-Based Feature Embedding of 4-D Light Fields for Compressive Imaging and Denoising
Author:
Funder
Research Grants Council, University Grants Committee
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s11263-023-01974-9.pdf
Reference77 articles.
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3. Beck, A., & Teboulle, M. (2009). Fast gradient-based algorithms for constrained total variation image denoising and deblurring problems. IEEE Transactions on Image Processing, 18(11), 2419–2434.
4. Chen, J., Hou, J., & Chau, L.-P. (2018). Light field denoising via anisotropic parallax analysis in a cnn framework. IEEE Signal Processing Letters, 25(9), 1403–1407.
5. Chen, J., Hou, J., Ni, Y., & Chau, L.-P. (2018). Accurate light field depth estimation with superpixel regularization over partially occluded regions. IEEE Transactions on Image Processing, 27(10), 4889–4900.
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