{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/hyperspectral-image-super-resolution-with","title":"Hyperspectral Image Super-Resolution With Optimized RGB Guidance","arxiv_id":null,"date":"2019-06-01","proceeding":"CVPR 2019 6","authors":["Ying Fu"," Tao Zhang"," Yinqiang Zheng"," Debing Zhang"," Hua Huang"],"abstract":" To overcome the limitations of existing hyperspectral cameras on   spatial/temporal resolution, fusing a low resolution hyperspectral image (HSI)   with a high resolution RGB (or multispectral) image into a high resolution HSI   has been prevalent. Previous methods for this fusion task usually employ   hand-crafted priors to model the underlying structure of the latent high   resolution HSI, and the effect of the camera spectral response (CSR) of the   RGB camera on super-resolution accuracy has rarely been investigated. In this   paper, we first present a simple and efficient convolutional neural network   (CNN) based method for HSI super-resolution in an unsupervised way, without   any prior training. Later, we append a CSR optimization layer onto the HSI   super-resolution network, either to automatically select the best CSR in a   given CSR dataset, or to design the optimal CSR under some physical   restrictions. Experimental results show our method outperforms the   state-of-the-arts, and the CSR optimization can further boost the accuracy of   HSI super-resolution.\r","url_abs":"http://openaccess.thecvf.com/content_CVPR_2019/html/Fu_Hyperspectral_Image_Super-Resolution_With_Optimized_RGB_Guidance_CVPR_2019_paper.html","url_pdf":"http://openaccess.thecvf.com/content_CVPR_2019/papers/Fu_Hyperspectral_Image_Super-Resolution_With_Optimized_RGB_Guidance_CVPR_2019_paper.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"hyperspectral-image-super-resolution-with","repo_url":"https://github.com/colintaozhang/hsi-sr","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"hyperspectral-image-super-resolution","task_name":"Hyperspectral Image Super-Resolution"},{"task_slug":"image-super-resolution","task_name":"Image Super-Resolution"},{"task_slug":"super-resolution","task_name":"Super-Resolution"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}