Title
View-Consistent Intrinsic Decomposition for Stereoscopic Images.
Abstract
In this paper, we focus on the intrinsic image decomposition problem for stereoscopic image pairs. The existing methods cannot be applied directly to decompose stereoscopic images, as it often produces inconsistent reflectance (albedo) and 3D artifacts after the decomposition. We propose a straightforward yet effective framework that enables a high-quality decomposition for stereoscopic pairs. First, retinex-based constraints are employed to coarsely classify the observed image gradients into two categories that are caused by reflectance changes and illumination variations, respectively. Second, reflectance-consistent constraints are added to control the reflectance consistency between the left and right views. Since this problem is highly ill-posed, we further analyze local and non-local image textures regularized by super-pixels within and across two views to reduce reflectance ambiguity. Lastly, absolute-scale constraints are employed to normalize the decomposition results. Extensive experiments on the real-world stereoscopic images and synthetic stereoscopic images reveal that our method can readily achieve high-quality decomposition performance.
Year
DOI
Venue
2019
10.1109/ACCESS.2019.2943516
IEEE ACCESS
Keywords
DocType
Volume
Stereo image processing,Image decomposition,Videos,Lighting,Task analysis,Surface treatment,Shape,Intrinsic image decomposition,reflectance,shading,stereoscopic image
Journal
7
ISSN
Citations 
PageRank 
2169-3536
0
0.34
References 
Authors
0
5
Name
Order
Citations
PageRank
Dehua Xie101.69
Shuaicheng Liu236328.26
Y. L. Wang312028.52
Shuyuan Zhu415624.72
Bing Zeng500.34