@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} }