Integrated cosparse analysis model with explicit edge inconsistency measurement for guided depth map upsampling

Yifan Zuo; Qiang Wu; Ping An; Xiwu Shang

doi:10.1117/1.JEI.27.4.043004

5 July 2018 Integrated cosparse analysis model with explicit edge inconsistency measurement for guided depth map upsampling

Yifan Zuo, Qiang Wu, Ping An, Xiwu Shang

Author Affiliations +

Journal of Electronic Imaging, Vol. 27, Issue 4, 043004 (July 2018). https://doi.org/10.1117/1.JEI.27.4.043004

Abstract

A low-resolution depth map can be upsampled through the guidance from the registered high-resolution color image. This type of method is so-called guided depth map upsampling. Among the existing methods based on Markov random field (MRF), either data-driven or model-based prior is adopted to construct the regularization term. The data-driven prior can implicitly reveal the relation between color-depth image pair by training on external data. The model-based prior provides the anisotropic smoothness constraint guided by high-resolution color image. These types of priors can complement each other to solve the ambiguity in guided depth map upsampling. An MRF-based approach is proposed that takes both of them into account to regularize the depth map. Based on analysis sparse coding, the data-driven prior is defined by joint cosparsity on the vectors transformed from color-depth patches using the pair of learned operators. It is based on the assumption that the cosupports of such bimodal image structures computed by the operators are aligned. The edge inconsistency measurement is explicitly calculated, which is embedded into the model-based prior. It can significantly mitigate texture-copying artifacts. The experimental results on Middlebury datasets demonstrate the validity of the proposed method that outperforms seven state-of-the-art approaches.

Citation Download Citation

Yifan Zuo, Qiang Wu, Ping An, and Xiwu Shang "Integrated cosparse analysis model with explicit edge inconsistency measurement for guided depth map upsampling," Journal of Electronic Imaging 27(4), 043004 (5 July 2018). https://doi.org/10.1117/1.JEI.27.4.043004

Received: 7 February 2018; Accepted: 15 June 2018; Published: 5 July 2018

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $24.00

Non-members: $28.00 ADD TO CART

JOURNAL ARTICLE
11 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Lawrencium

Data modeling

Model-based design

Integrated modeling

Magnetorheological finishing

Volume rendering

Performance modeling

Show All Keywords

Keywords/Phrases

Search In:

Publication Years