We cannot guarantee that the final estimated HR image is overall optimal, because the entire MVSR reconstruction was divided into two stages in [3, 7, 8, 9].
In Section 2 we introduce the MVSR forward model, and the manner in which an MVSR problem is reformulated into an MCBD problem.
In this section, we compare the proposed method with SR-FVS , SR-FVS + ScSR  and depth-based MVSR method .
This study proposed a new MVSR method that addresses MVSR by solving an MCBD problem using the ADMM.
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A super-resolution-free-viewpoint image synthesis (SR-FVS) method that used adaptive regularization for MVSR to address depth inaccuracies was proposed by Takahashi; this method simultaneously realized free-viewpoint image SR and free-viewpoint depth estimation .
In Section 2, we introduce a mathematical model that corresponds to the proposed MVSR method and illustrates its reformulation into the IF problem and the BD problem.
This study has proposed a depth-based MVSR approach, in which MVSR is addressed by solving an IF problem based on the depth map of the desired image and a BD problem using ADMM.
Propose an MVSR framework that jointly realizes IF and solves BD, such that the final estimated HR image is of higher quality;