@Article{cmc.2020.05777,
AUTHOR = {Tingting Yang, Shuwen Jia, Hao Ma},
TITLE = {Research on the Application of Super Resolution Reconstruction Algorithm for Underwater Image},
JOURNAL = {Computers, Materials \& Continua},
VOLUME = {62},
YEAR = {2020},
NUMBER = {3},
PAGES = {1249--1258},
URL = {http://www.techscience.com/cmc/v62n3/38352},
ISSN = {1546-2226},
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.},
DOI = {10.32604/cmc.2020.05777}
}