Tingting Yang1, Shuwen Jia1, Hao Ma2, *
CMC-Computers, Materials & Continua, Vol.62, No.3, pp. 1249-1258, 2020, DOI: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 More >
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