A novel algorithm for color constancy
International Journal of Computer Vision
The image processing handbook
A Flexible New Technique for Camera Calibration
IEEE Transactions on Pattern Analysis and Machine Intelligence
Color by Correlation: A Simple, Unifying Framework for Color Constancy
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Computer Graphics and Applications
A Variational Framework for Retinex
International Journal of Computer Vision
Keyframe-based tracking for rotoscoping and animation
ACM SIGGRAPH 2004 Papers
A robust Kalman filter design for image restoration
ICASSP '01 Proceedings of the Acoustics, Speech, and Signal Processing, 2001. on IEEE International Conference - Volume 03
Automated colour grading using colour distribution transfer
Computer Vision and Image Understanding
An effective algorithm for image sequence color transfer
Mathematical and Computer Modelling: An International Journal
A computational model for color naming and describing color composition of images
IEEE Transactions on Image Processing
A survey of perceptual evaluations and requirements of three-dimensional TV
IEEE Transactions on Circuits and Systems for Video Technology
Motion and Disparity Compensated Coding for Multiview Video
IEEE Transactions on Circuits and Systems for Video Technology
Multiview Video Coding Using View Interpolation and Color Correction
IEEE Transactions on Circuits and Systems for Video Technology
Colorimetric correction for stereoscopic camera arrays
ACCV'12 Proceedings of the 11th international conference on Computer Vision - Volume Part I
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Color correction is a necessary operation in multi-view video processing, because color tends to be influenced by camera characteristic, surface reflectance or scene illumination. To achieve high-quality correction results, a new color correction method, based on the theoretical model of multi-view imaging and image restoration, is proposed in this paper. Considering the illumination problem in multi-view imaging, foreground and background regions are separated from images and dominant color extraction is used only for background regions of reference and input images, so that uniform reference surface information is used. Then, color correction is extended to video sequences with a tracking approach. Furthermore, an objective performance evaluation is proposed to evaluate the color correction. We present a variety of results for different test sequences, arguing that background-based method outperforms foreground-based method, and better subjective and objective visual effect can be achieved for images as well as videos.