130060 20240122171020.0 doi 10.1016/j.cag.2019.06.011 sideral 112574 ART-2019-112574 eng Molino, Fernando del Polarization mapping 2019 Photographers use the hardware of the camera (aperture, exposure time...), lens and filters as tools for artistic expressivity. This expressivity has often been enhanced by software, such as high dynamic range images have been edited in post-process with software tone mappers. In this paper, we propose a similar approach with polarization filters: we design a capture process that enables us to acquire a Stokes image (that encodes all the possible light polarization states) with a single camera, and we then offer a set of software tools that can apply any common polarization filter as a software post-process, delaying the choice of the adequate filter and enabling filters that can be mathematically modeled but are not available as hardware. Then, we devise and provide new algorithms that automatically select the optimal filter for specific goals, such as maximizing (or minimizing) brightness, contrast or saturation. We later show how such optimization filters can not only be applied to the whole image, but can also be at per-pixel level, obtaining new interesting effects. Such optimization can work at real time rates, fact that is illustrated with a brush based user editing interactive tool. The different types of filters are tested in a wide range of results. Access copy available to the general public Unrestricted info:eu-repo/grantAgreement/EC/H2020/682080/EU/Intuitive editing of visual appearance from real-world datasets/CHAMELEON This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 682080-CHAMELEON info:eu-repo/grantAgreement/ES/MINECO/TIN2016-78753-P info:eu-repo/semantics/openAccess by-nc-nd http://creativecommons.org/licenses/by-nc-nd/3.0/es/ 1.351 2019 COMPUTER SCIENCE, SOFTWARE ENGINEERING 65 / 107 = 0.607 2019 Q3 T2 0.571 2019 Engineering (miscellaneous) 2019 Q1 Software 2019 Q2 Human-Computer Interaction 2019 Q2 Signal Processing 2019 Q2 Computer Graphics and Computer-Aided Design 2019 Q2 Computer Vision and Pattern Recognition 2019 Q2 info:eu-repo/semantics/article info:eu-repo/semantics/acceptedVersion Muñoz, Adolfo Universidad de Zaragoza (orcid)0000-0002-8160-7159 5007 570 Universidad de Zaragoza Dpto. Informát.Ingenie.Sistms. Área Lenguajes y Sistemas Inf. 83 (2019), 42-50 Comput. graph. COMPUTERS & GRAPHICS-UK 0097-8493 540428 http://zaguan.unizar.es/record/130060/files/texto_completo.pdf Postprint 1980315 http://zaguan.unizar.es/record/130060/files/texto_completo.jpg?subformat=icon icon Postprint oai:zaguan.unizar.es:130060 articulos driver 2024-01-22-15:23:35 ARTICLE