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A New Method of Image Restoration Technology Based on WGAN.
- Source :
- Computer Systems Science & Engineering; 2022, Vol. 41 Issue 2, p689-698, 10p
- Publication Year :
- 2022
-
Abstract
- With the development of image restoration technology based on deep learning, more complex problems are being solved, especially in image semantic inpainting based on context. Nowadays, image semantic inpainting techniques are becoming more mature. However, due to the limitations of memory, the instability of training, and the lack of sample diversity, the results of image restoration are still encountering difficult problems, such as repairing the content of glitches which cannot be well integrated with the original image. Therefore, we propose an image inpainting network based on Wasserstein generative adversarial network (WGAN) distance. With the corresponding technology having been adjusted and improved, we attempted to use the Adam algorithm to replace the traditional stochastic gradient descent, and another algorithm to optimize the training used in recent years. We evaluated our algorithm on the ImageNet dataset. We obtained high-quality restoration results, indicating that our algorithm improves the clarity and consistency of the image. [ABSTRACT FROM AUTHOR]
- Subjects :
- IMAGE reconstruction
DEEP learning
SEMANTICS
IMAGE processing
ALGORITHMS
Subjects
Details
- Language :
- English
- ISSN :
- 02676192
- Volume :
- 41
- Issue :
- 2
- Database :
- Complementary Index
- Journal :
- Computer Systems Science & Engineering
- Publication Type :
- Academic Journal
- Accession number :
- 161570333
- Full Text :
- https://doi.org/10.32604/csse.2022.020176