A competent image denoising method based on structural information extraction-Reference-Cited by-同舟云学术

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A competent image denoising method based on structural information extraction

Published:2022-06-26 Issue: Volume: Page:
ISSN:0178-2789
Container-title:The Visual Computer
language:en
Short-container-title:Vis Comput

Author:

Shi Miaowen^ORCID,Fan Linwei,Li Xuemei,Zhang Caiming

Funder

National Natural Science Foundation of China

Science and Technology Innovation Program for Distributed Young Talents of Shandong Province Higher Education Institutions

Natural Science Foundation of Shandong Province

Publisher

Springer Science and Business Media LLC

Subject

Computer Graphics and Computer-Aided Design,Computer Vision and Pattern Recognition,Software

Link

https://link.springer.com/content/pdf/10.1007/s00371-022-02491-5.pdf

Reference55 articles.

1. Morikawa, C., Kobayashi, M., Satoh, M., et al.: Image and video processing on mobile devices: a survey. Vis. Comput. 37, 2931–2949 (2021). https://doi.org/10.1007/s00371-021-02200-8

2. Antoni, B., Coll, B., Morel, J.-M.: A review of image denoising algorithms, with a new one. Multisc. Model. Simul. 4(2), 490–530 (2005). https://doi.org/10.1137/040616024

3. Fan, L., Zhang, F., Fan, H., et al.: Brief review of image denoising techniques. Vis. Comput. Ind. Biomed. Art 2(1), 1–12 (2019). https://doi.org/10.9756/sijcsea/v3i1/03020060201

4. Carlo, T., Manduchi, R.: Bilateral filtering for gray and color images. In: Sixth international conference on computer vision, pp. 839–846. https://doi.org/10.1109/ICCV.1998.710815

5. Rudin, L.I., Osher, S., Fatemi, E.: Nonlinear total variation based noise removal algorithms. Phys. D Nonlinear Phenomena 60(1–4), 259–268 (1992). https://doi.org/10.1016/0167-2789(92)90242-F

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