A PARALLEL LEAP-FROG ALGORITHM FOR 3-SOURCE PHOTOMETRIC STEREO

Abstract

The School of Computer Science and Software EngineeringThe University of Western Australia35 Stirling HighwayCrawley, W. A., 6009, Perth, AustraliaAbstract Existing Photometric Stereo methods provide reasonable surface reconstructionsunless the irradiance image is corrupted with noise and effects of digitisation.However, in real world situations the measured image is almost always cor-rupted, so an efficient method must be formulated to denoise the data. Oncenoise is added at the level of the images the noisy Photometric Stereo problemwith a least squares estimate is transformed into a non-linear discrete optimiza-tion problem depending on a large number of parameters. One of the compu-tationally feasible methods of performing this non-linear optimization is to usemany smaller local optimizations to find a minimum (called 2D Leap-Frog).However, this process still takes a large amount of time using a single processor,and when realistic image resolutions are used this method becomes impractical.This paper presents a parallel implementation of the 2D Leap-Frog algorithm inorder to provide an improvement in the time complexity. While the focus of thisresearch is in the area of shape from shading, the iterative scheme for finding alocal optimum for a large number of parameters can also be applied to any op-timization problems in Computer Vision. The results presented herein supportthe hypothesis that a high speed up and high efficiency can be achieved using aparallel method in a distributed shared memory environment.Keywords: Photometric Stereo, Shape from Shading, Nonlinear Optimization, Parallel Pro-cessing, Noise Rectification.