11 November 2020 Robust illumination invariant depth recovery by combining local phase and intensity information of images
Feifei Gu, Huazhao Cao, Juan Zhao, Jing Liu, Fang Liu, Zhan Song
Author Affiliations +
Abstract

Both intensity and phase information of images have been the most important similarity measures in solving the general stereo matching problem. Intensity contains most of the imaging information of the scene/object, yet the phase information could reflect the local structure of images, which is more robust than the grayscale value. Plenty of work has been done in intensity-based or phase-based stereo matching methods. However, neither of them could work well enough when process images were taken under varied illuminations. A robust depth recovery method by making use of both intensity and phase information of stereo images properly is proposed. Firstly, 2D signal analysis is conducted by using the multiscale monogenic wavelet transform, from which local phase and intensity amplitude information are extracted into different scales. Secondly, disparity maps are estimated in different scales based on the intensity information. Thirdly, the optimal disparity is obtained by weighted-combining the disparity maps in different scales. The weighted coefficients are computed by making use of the phase information. Extensive experimental evaluation demonstrates the benefits of the proposed method.

© 2020 Society of Photo-Optical Instrumentation Engineers (SPIE) 0091-3286/2020/$28.00 © 2020 SPIE
Feifei Gu, Huazhao Cao, Juan Zhao, Jing Liu, Fang Liu, and Zhan Song "Robust illumination invariant depth recovery by combining local phase and intensity information of images," Optical Engineering 59(11), 113101 (11 November 2020). https://doi.org/10.1117/1.OE.59.11.113101
Received: 24 July 2020; Accepted: 23 October 2020; Published: 11 November 2020
Lens.org Logo
CITATIONS
Cited by 1 scholarly publication.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Optical engineering

Point spread functions

Error analysis

Image filtering

Electronic filtering

Transform theory

Image analysis

RELATED CONTENT


Back to Top