Color Alignment for Relative Color Constancy via Non-Standard References

Autor: Yunfeng Zhao, Stuart Ferguson, Huiyu Zhou, Christopher Elliott, Karen Rafferty

Publikováno v: Zhao, Y, Ferguson, S, Zhou, H, Elliott, C & Rafferty, K 2022, ' Colour alignment for relative colour constancy via non-standard references ', IEEE Transactions on Image Processing, vol. 31, pp. 6591-6604 . https://doi.org/10.1109/TIP.2022.3214107, https://doi.org/10.1109/TIP.2022.3214107

Relative colour constancy is an essential requirement for many scientific imaging applications. However, most digital cameras differ in their image formations and native sensor output is usually inaccessible, e.g., in smartphone camera applications.

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ce2c91c120216075a8c84d633e450d01
https://doi.org/10.1109/tip.2022.3214107

Representing camera response function by a single latent variable and fully connected neural network

Autor: Zhao, Yunfeng, Ferguson, Stuart, Zhou, Huiyu, Rafferty, Karen

Publikováno v: Zhao, Y, Ferguson, S, Zhou, H & Rafferty, K 2022, ' Representing camera response function by a single latent variable and fully connected neural network ', Signal, Image and Video Processing . https://doi.org/10.1007/s11760-022-02351-8

Modelling the mapping from scene irradiance to image intensity is essential for many computer vision tasks. Such mapping is known as the camera response. Most digital cameras use a nonlinear function to map irradiance, as measured by the sensor to an

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b369b84317eb6caa2c2099ff0bec96be
https://pure.qub.ac.uk/en/publications/ef631a8b-f7d2-41c0-af74-b73a4e938899