In order to improve the spatial resolution of hyperspectral images, this paper improves the network structure of SSRNET algorithm and analyzes the functions of various parts of the network model. A comparative experimental analysis was carried out on the urban dataset. Experimental results show that the improved method in this paper has improved to a certain extent in both subjective and objective evaluation.
Multi-source remote sensing image fusion is a data processing technology that complements two or more remote sensing images taken from the same target of multiple sensors to obtain more accurate and perfect comprehensive images. Image fusion is not only an important part of remote sensing detection data processing, but also has a wide range of applications in environmental detection, precision agriculture, urban planning and other fields. Based on the method of component substitution, this paper discusses the image fusion methods of Brovey transform, IHS transformation, PCA transformation and weighted fusion, and performs fusion experiments and analyses on four methods, and finally summarizes and makes prospects.
Image segmentation is an important branch in the field of artificial intelligence and an important part of image understanding in machine vision technology. Based on computer vision, this paper makes a classification study on image segmentation technology, including the basic method of image segmentation, image edge detection algorithm and the application of connected area analysis, area growth, watershed and other algorithmic ideas to achieve image segmentation. In the basic method of image segmentation, the adaptive segmentation method and otsu method processing effect and processing range are better, in image edge extraction, the canny operator processing effect is obviously higher than other operators.
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