国产欧美精品一区二区,中文字幕专区在线亚洲,国产精品美女网站在线观看,艾秋果冻传媒2021精品,在线免费一区二区,久久久久久青草大香综合精品,日韩美aaa特级毛片,欧美成人精品午夜免费影视

Remote sensing images are highly susceptible to environmental and weather factors, resulting in reduced resolution. In order to improve the quality of extracting detailed information from a single remote sensing image, a super-resolution reconstruction method for a single remote sensing image is optimized and designed with the support of fusion residual networks and texture transfer models. Considering the degradation phenomenon of remote sensing images, according to the principles of remote sensing imaging, obtain a single low resolution remote sensing image. By performing steps such as defogging, smoothing filtering, and color space conversion, the assignment of initial remote sensing images is achieved. By integrating residual networks and texture transfer models, single remote sensing image texture feature labeling is performed to determine the image reconstruction pattern. After compensating for image detail loss, the super-resolution reconstruction results of a single remote sensing image are obtained. Taking remote sensing images of different sizes as the research objective, the experimental results show that the proposed method improves the peak signal-to-noise ratio of the reconstructed image by about 204, and the resolution of the reconstructed image is always 1080dpi. At the same time, the time cost of the image reconstruction task is significantly reduced