ArticleJournal of imaging2023
Spectral Super-Resolution for High Dynamic Range Images.
Article in Journal of imaging, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
5 authors.
Funding
Abstract
The images we commonly use are RGB images that contain three pieces of information: red, green, and blue. On the other hand, hyperspectral (HS) images retain wavelength information. HS images are utilized in various fields due to their rich information content, but acquiring them requires specialized and expensive equipment that is not easily accessible to everyone. Recently, Spectral Super-Resolution (SSR), which generates spectral images from RGB images, has been studied. Conventional SSR methods target Low Dynamic Range (LDR) images. However, some practical applications require High Dynamic Range (HDR) images. In this paper, an SSR method for HDR is proposed. As a practical example, we use the HDR-HS images generated by the proposed method as environment maps and perform spectral image-based lighting. The rendering results by our method are more realistic than conventional renderers and LDR SSR methods, and this is the first attempt to utilize SSR for spectral rendering.
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Registered trials
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