%A An ZHU, Chu XU %T Method for super-resolution using parallel interlaced sampling %0 Journal Article %D 2020 %J Journal of Shandong University(Engineering Science) %R 10.6040/j.issn.1672-3961.0.2019.318 %P 10-16 %V 50 %N 2 %U {http://gxbwk.njournal.sdu.edu.cn/CN/abstract/article_1904.shtml} %8 2020-04-20 %X

Various Internet-based images and artificial intelligence applications were more sensitive to the quality of image data. The image quality had been seriously affected due to the limitations of previous acquisition equipment and transmission methods. In order to compensate for the loss of image data quality and enhance the image effect, a parallel interlaced up and down sampling network (PSUDN) was proposed as a better solution to this problem, which using parallel high resolution feature (HR Feature) and low resolution feature (LR Feature) interleaving sample to generated advanced feature maps, and improved the quality of the output high-resolution pictures by building parallel high resolution feature modules and low resolution feature modules. The model constructed by parallel upsampling and downsampling could reconstruct 8 times high resolution pictures and achieved better results.