Mathematical Problems in Engineering
Volume 2011 (2011), Article ID 202653, 14 pages
Research Article

A Multi-Model Stereo Similarity Function Based on Monogenic Signal Analysis in Poisson Scale Space

1State Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
2Xi'an Research Institute of Hi-Tech, Hongqing Town, Xi'an, Shaanxi 710025, China

Received 28 July 2010; Revised 15 November 2010; Accepted 20 March 2011

Academic Editor: Katica R. (Stevanovic) Hedrih

Copyright © 2011 Jinjun Li et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


A stereo similarity function based on local multi-model monogenic image feature descriptors (LMFD) is proposed to match interest points and estimate disparity map for stereo images. Local multi-model monogenic image features include local orientation and instantaneous phase of the gray monogenic signal, local color phase of the color monogenic signal, and local mean colors in the multiscale color monogenic signal framework. The gray monogenic signal, which is the extension of analytic signal to gray level image using Dirac operator and Laplace equation, consists of local amplitude, local orientation, and instantaneous phase of 2D image signal. The color monogenic signal is the extension of monogenic signal to color image based on Clifford algebras. The local color phase can be estimated by computing geometric product between the color monogenic signal and a unit reference vector in RGB color space. Experiment results on the synthetic and natural stereo images show the performance of the proposed approach.