This article considers techniques for accelerating a light field reconstruction algorithm operating in shearlet domain. In the proposed approach, an independent reconstruction of epipolar images (EPIs) is replaced with a consecutive tree-structured reconstruction. It aims at decreasing the number of iterations necessary for an EPI reconstruction by using already processed EPIs as initial values in the reconstruction stage. Two algorithms for structuring such processing trees are presented. The reconstruction performance of the proposed algorithms is illustrated on a real dataset. The underlying differences between the algorithms are discussed and numerical results of computation speeds are presented.Peer reviewe
In this paper, we present a novel approach for light field retrieval in the transformed domain. The ...
In this paper, we present a novel approach for recovering high resolution light fields from input da...
International audienceThis paper considers the compressive sensing framework as a way of overcoming ...
We consider the problem of reconstructing densely sampled light field (DSLF) from sparse camera view...
In this article we develop an image based rendering technique based on light field reconstruction fr...
Shearlet Transform (ST) has been instrumental for the Densely-Sampled Light Field (DSLF) reconstruct...
Light fields representing Lambertian scenes are characterized by specific epipolar plane images, whi...
Shearlet Transform (ST) is one of the most effective algorithms for the Densely-Sampled Light Field ...
The emerging light-field and holographic displays aim at providing an immersive visual experience, w...
The performance of a light field reconstruction algorithm is typically affected by the disparity ran...
Shearlet Transform (ST) is one of the most effective approaches for light field reconstruction from ...
Figure 1: Our method reconstructs accurate depth from light fields of complex scenes. The images on ...
Light field acquisition technologies capture angular and spatial information ofthe scene. The spatia...
Shearlet Transform (ST) is one of the most effective methods for Densely-Sampled Light Field (DSLF) ...
In this chapter, we motivate the use of densely-sampled light fields as the representation which can...
In this paper, we present a novel approach for light field retrieval in the transformed domain. The ...
In this paper, we present a novel approach for recovering high resolution light fields from input da...
International audienceThis paper considers the compressive sensing framework as a way of overcoming ...
We consider the problem of reconstructing densely sampled light field (DSLF) from sparse camera view...
In this article we develop an image based rendering technique based on light field reconstruction fr...
Shearlet Transform (ST) has been instrumental for the Densely-Sampled Light Field (DSLF) reconstruct...
Light fields representing Lambertian scenes are characterized by specific epipolar plane images, whi...
Shearlet Transform (ST) is one of the most effective algorithms for the Densely-Sampled Light Field ...
The emerging light-field and holographic displays aim at providing an immersive visual experience, w...
The performance of a light field reconstruction algorithm is typically affected by the disparity ran...
Shearlet Transform (ST) is one of the most effective approaches for light field reconstruction from ...
Figure 1: Our method reconstructs accurate depth from light fields of complex scenes. The images on ...
Light field acquisition technologies capture angular and spatial information ofthe scene. The spatia...
Shearlet Transform (ST) is one of the most effective methods for Densely-Sampled Light Field (DSLF) ...
In this chapter, we motivate the use of densely-sampled light fields as the representation which can...
In this paper, we present a novel approach for light field retrieval in the transformed domain. The ...
In this paper, we present a novel approach for recovering high resolution light fields from input da...
International audienceThis paper considers the compressive sensing framework as a way of overcoming ...