Vol.62, No.3, 2020, pp.1249-1258, doi:10.32604/cmc.2020.05777
Research on the Application of Super Resolution Reconstruction Algorithm for Underwater Image
  • Tingting Yang1, Shuwen Jia1, Hao Ma2, *
1 University of Sanya, Sanya, 572000, China.
2 1455 Boulevard de Maisonneuve O, Montréal, QC H3G 1M8, Canada.
* Corresponding Author: Tingting Yang. Email: .
Underwater imaging is widely used in ocean, river and lake exploration, but it is affected by properties of water and the optics. In order to solve the lower-resolution underwater image formed by the influence of water and light, the image super-resolution reconstruction technique is applied to the underwater image processing. This paper addresses the problem of generating super-resolution underwater images by convolutional neural network framework technology. We research the degradation model of underwater images, and analyze the lower-resolution factors of underwater images in different situations, and compare different traditional super-resolution image reconstruction algorithms. We further show that the algorithm of super-resolution using deep convolution networks (SRCNN) which applied to super-resolution underwater images achieves good results.
Underwater image, image super-resolution algorithm, algorithm reconstruction, degradation model.
Cite This Article
. , "Research on the application of super resolution reconstruction algorithm for underwater image," Computers, Materials & Continua, vol. 62, no.3, pp. 1249–1258, 2020.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.