The Effect of Light Field Reconstruction and Angular Resolution Reduction on the Quality of Experience

Author(s):  
Peter A. Kara ◽  
Peter T. Kovacs ◽  
Suren Vagharshakyan ◽  
Maria G. Martini ◽  
Attila Barsi ◽  
...  
2016 ◽  
Vol 24 (12) ◽  
pp. 726-740 ◽  
Author(s):  
Shizheng Wang ◽  
Kien Seng Ong ◽  
Phil Surman ◽  
Junsong Yuan ◽  
Yuanjin Zheng ◽  
...  

Micromachines ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 557
Author(s):  
Xingzheng Wang ◽  
Yongqiang Zan ◽  
Senlin You ◽  
Yuanlong Deng ◽  
Lihua Li

There is a trade-off between spatial resolution and angular resolution limits in light field applications; various targeted algorithms have been proposed to enhance angular resolution while ensuring high spatial resolution simultaneously, which is also called view synthesis. Among them, depth estimation-based methods can use only four corner views to reconstruct a novel view at an arbitrary location. However, depth estimation is a time-consuming process, and the quality of the reconstructed novel view is not only related to the number of the input views, but also the location of the input views. In this paper, we explore the relationship between different input view selections with the angular super-resolution reconstruction results. Different numbers and positions of input views are selected to compare the speed of super-resolution reconstruction and the quality of novel views. Experimental results show that the speed of the algorithm decreases with the increase of the input views for each novel view, and the quality of the novel view decreases with the increase of the distance from the input views. After comparison using two input views in the same line to reconstruct the novel views between them, fast and accurate light field view synthesis is achieved.


Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 2919
Author(s):  
You-Na Jin ◽  
Chae-Eun Rhee

Multi-view or light field images have recently gained much attraction from academic and commercial fields to create breakthroughs that go beyond simple video-watching experiences. Immersive virtual reality is an important example. High image quality is essential in systems with a near-eye display device. The compression efficiency is also critical because a large amount of multi-view data needs to be stored and transferred. However, noise can be easily generated during image capturing, and these noisy images severely deteriorate both the quality of experience and the compression efficiency. Therefore, denoising is a prerequisite to produce multi-view-based image contents. In this paper, the structural characteristics of linear multi-view images are fully utilized to increase the denoising speed and performance as well as to improve the compression efficiency. Assuming the sequential processes of denoising and compression, multi-view geometry-based denoising is performed keeping the temporal correlation among views. Experimental results show the proposed scheme significantly improves the compression efficiency of denoised views up to 76.05%, maintaining good denoising quality compared to the popular conventional denoise algorithms.


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