Open Access
ARTICLE
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: .
Computers, Materials & Continua 2020, 62(3), 1249-1258. https://doi.org/10.32604/cmc.2020.05777
Abstract
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.
Keywords
Cite This Article
T. Yang, S. Jia and H. Ma, "Research on the application of super resolution reconstruction algorithm for underwater image,"
Computers, Materials & Continua, vol. 62, no.3, pp. 1249–1258, 2020. https://doi.org/10.32604/cmc.2020.05777
Citations