Paper Info
Title
Conjugate Gradient In Noisy Photometric Stereo
Abstract
This paper discusses the problem of reconstructing the Lambertian surface from noisy three-light source Photometric Stereo. In the continuous image setting the shape recovery process is divided into two steps: an algebraic one (gradient computation) and analytical one (gradient integration). The digitized case with added noise has it discrete analogue in which also perturbed gradient from three noisy images is first computed. Generically such non-integrable vector field is subsequently rectified to the "closest" integrable one. Finally, numerical integration scheme yields the unknown surface. The process of vector field rectification is reduced to the corresponding linear optimization task of very high dimension (comparable with the image resolution). Standard methods based on matrix pseudo-inversion suffer from heavy computation due to the necessity of large matrix inversion. A possible alternative is to set up an iterative scheme based on local snapshots' optimizations (e.g. 2D-Leap-Frog). Another approach which is proposed in this paper is solving the above global optimization scheme by Conjugate Gradient with no inversion of matrices of large dimension. The experimental results from this paper show that the application of Conjugate Gradient forms a computationally feasible alternative in denoising Photometric Stereo.
Year
DOI
Venue
2014
10.1007/978-3-319-11331-9_41
COMPUTER VISION AND GRAPHICS, ICCVG 2014
Keywords
Field
DocType
Shape Reconstruction, Photometric Stereo, noise removal, Conjugate Gradient, numerical computation
Conjugate gradient method,Noise reduction,Computer vision,Global optimization,Matrix (mathematics),Computer science,Vector field,Numerical integration,Algorithm,Artificial intelligence,Image resolution,Photometric stereo
Conference
Volume
ISSN
Citations 
8671
0302-9743
2
PageRank 
References 
Authors
0.38
11
2
Name
Order
Citations
PageRank
Ryszard Kozera116326.54
Felicja Okulicka-Dluzewska251.84