Reflection component separation using statistical analysis and polarisation

Authors:
Lichi Zhang;Edwin R. Hancock;Gary A. Atkinson
Affiliations:
Department of Computer Science, University of York and Machine Vision Laboratory, University of the West of England, UK;Department of Computer Science, University of York and Machine Vision Laboratory, University of the West of England, UK;Department of Computer Science, University of York and Machine Vision Laboratory, University of the West of England, UK
Venue:
IbPRIA'11 Proceedings of the 5th Iberian conference on Pattern recognition and image analysis
Year:
2011

Citing 11
Cited 1

Constraining Object Features Using a Polarization Reflectance Model

IEEE Transactions on Pattern Analysis and Machine Intelligence
Separation of Reflection Components Using Color and Polarization

International Journal of Computer Vision
Computer Vision: A Modern Approach

Computer Vision: A Modern Approach
Highlight Removal Using Shape-from-Shading

ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part II
Estimation of Diffuse and Specular Appearance

ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Transparent Surface Modeling from a Pair of Polarization Images

IEEE Transactions on Pattern Analysis and Machine Intelligence
Separation of Diffuse and Specular Components of Surface Reflection by Use of Polarization and Statistical Analysis of Images

IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape Estimation Using Polarization and Shading from Two Views

IEEE Transactions on Pattern Analysis and Machine Intelligence
Two-dimensional BRDF estimation from polarisation

Computer Vision and Image Understanding
Polarization vision: a new sensory approach to image understanding

Image and Vision Computing
Rapid acquisition of specular and diffuse normal maps from polarized spherical gradient illumination

EGSR'07 Proceedings of the 18th Eurographics conference on Rendering Techniques

Estimating surface characteristics and extracting features from polarisation

SSPR'12/SPR'12 Proceedings of the 2012 Joint IAPR international conference on Structural, Syntactic, and Statistical Pattern Recognition

Quantified Score

Hi-index	0.00

Visualization

Abstract

We show how to cast the problem of specularity subtraction as blind source separation from polarisation images. We commence by summarizing the relationships between the specular and diffuse reflection components for polarised images. We show how to use singular value decomposition for component separation. In particular, we show how reliable results can be obtained using three images acquired with different polariser angles under diffuse reflection. The proposed method can be used as the preprocessing step in shape from shading, segmentation, reflectance estimation and many other computer vision applications.