Abstract
We propose a ghost-free high dynamic range (HDR) image synthesis algorithm using a rank minimization framework. Based on the linear dependency among irradiance maps from low dynamic range (LDR) images, we formulate ghost-free HDR imaging as a low-rank matrix completion problem. The main contribution is to solve it efficiently via the augmented Lagrange multiplier (ALM) method, where the optimization variables are updated by closed-form solutions. Experiments on real image sets show that the proposed algorithm provides comparable or even better image qualities than state-of-the-art approaches, while demanding lower computational resources.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
