Manual of Photography: Photographic and Digital Imaging
Manual of Photography: Photographic and Digital Imaging
Gamut Constrained Illuminant Estimation
International Journal of Computer Vision
Interactive local adjustment of tonal values
ACM SIGGRAPH 2006 Papers
A Closed Form Solution to Natural Image Matting
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
ACM SIGGRAPH 2007 papers
Real-time edge-aware image processing with the bilateral grid
ACM SIGGRAPH 2007 papers
AppProp: all-pairs appearance-space edit propagation
ACM SIGGRAPH 2008 papers
Light mixture estimation for spatially varying white balance
ACM SIGGRAPH 2008 papers
Color constancy based on local space average color
Machine Vision and Applications
User-assisted intrinsic images
ACM SIGGRAPH Asia 2009 papers
Illumination decomposition for material recoloring with consistent interreflections
ACM SIGGRAPH 2011 papers
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Intrinsic images using optimization
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Color Constancy for Multiple Light Sources
IEEE Transactions on Image Processing
CVPR '12 Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
User-assisted image compositing for photographic lighting
ACM Transactions on Graphics (TOG) - SIGGRAPH 2013 Conference Proceedings
A sparse control model for image and video editing
ACM Transactions on Graphics (TOG)
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Proper white balance is essential in photographs to eliminate color casts due to illumination. The single-light case is hard to solve automatically but relatively easy for humans. Unfortunately, many scenes contain multiple light sources such as an indoor scene with a window, or when a flash is used in a tungsten-lit room. The light color can then vary on a per-pixel basis and the problem becomes challenging at best, even with advanced image editing tools. We propose a solution to the ill-posed mixed light white balance problem, based on user guidance. Users scribble on a few regions that should have the same color, indicate one or more regions of neutral color, and select regions where the current color looks correct. We first expand the provided scribble groups to more regions using pixel similarity and a robust voting scheme. We formulate the spatially varying white balance problem as a sparse data interpolation problem in which the user scribbles and their extensions form constraints. We demonstrate that our approach can produce satisfying results on a variety of scenes with intuitive scribbles and without any knowledge about the lights.