NDLI: View's dependency and low-rank background-guided compressed sensing for multi-view image joint reconstruction

Content Provider	IET Digital Library
Author	Fei, Xuan Li, Lei Cao, Heling Miao, Jianyu Yu, Renping
Abstract	Compressed sensing (CS) multi-camera network reconstruction has attracted much attention in the field of distributed CS networks. However, many multi-camera network reconstructions based on CS usually recover every image separately; the view's dependency and geometrical structure among these multi-view images could be rarely considered in this way, which will result in some unsatisfied joint reconstruction results. Here, the authors introduce to extract the multiple view geometry from multi-view images to construct the view's dependency observation model. Based on the proposed parametric transformation observation model, they propose a novel CS joint reconstruction method of multi-view image that guided by the spatial correlation and low-rank background constraints. The eventual optimisation model could be relaxed to a series of convex optimisation problems, which could be efficiently solved by combining the variable splitting and alternate iteration technique. The extended experimental results indicate that they proposed method has achieved a remarkable improvement in both objective criterion and visual fidelity compared with other competitive reconstruction methods.
Starting Page	2294
Ending Page	2303
Page Count	10
ISSN	17519659
Volume Number	13
e-ISSN	17519667
Issue Number	Issue 12, Oct (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/13/12
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2019.0295
Journal	IET Image Processing
Publisher Date	2019-08-07
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Camera Competitive Reconstruction Method Compressed Sensing Compressed Sensing Multicamera Network Reconstruction Computer Vision And Image Processing Technique Convex Programming CS Joint Reconstruction Method Distributed CS Network Image Reconstruction Interpolation And Function Approximation Iterative Method Low-rank Background Constraint Low-rank Background-guided Multicamera Network Reconstructions Multiple View Geometry Multiview Image Joint Reconstruction Numerical Analysis Optical, Image And Video Signal Processing Optimisation Spatial Correlation Unsatisfied Joint Reconstruction Result
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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