Paper
2 December 2011 A novel radiometric projector compensation algorithm based on Lambertian reflection model
Bo Zhu, Lijun Xie, Tingjun Yang, Qihui Wang, Yao Zheng
Author Affiliations +
Proceedings Volume 8004, MIPPR 2011: Pattern Recognition and Computer Vision; 80040I (2011) https://doi.org/10.1117/12.901092
Event: Seventh International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2011), 2011, Guilin, China
Abstract
In this paper, a novel radiometric compensation algorithm based on Lambertian reflection model is proposed to neutralize the visual perception of colors and textures which are intrinsic to the projection display surface. The algorithm uses a calibration method of advanced coded structure light to determine the geometric mapping between corresponding points in the projector-camera system. Concrete analysis of the dynamic range of projectors is applied to obtain the intensity limits of the input image. Consequently, the Lambertian reflection model is constructed for each point to compute the radiometric compensation function between displayed images and camera captured images. Experimental results show that this algorithm can effectively correct color inaccuracy of projection on arbitrary textured surfaces, and observers almost hard to notice visible artifacts of projected images.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Bo Zhu, Lijun Xie, Tingjun Yang, Qihui Wang, and Yao Zheng "A novel radiometric projector compensation algorithm based on Lambertian reflection model", Proc. SPIE 8004, MIPPR 2011: Pattern Recognition and Computer Vision, 80040I (2 December 2011); https://doi.org/10.1117/12.901092
Lens.org Logo
CITATIONS
Cited by 5 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Reflection

Projection systems

RGB color model

Visual process modeling

Calibration

Cameras

Visualization

Back to Top