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Tensor-Based Light Field Denoising by Integrating Super-Resolution | IEEE Conference Publication | IEEE Xplore

Tensor-Based Light Field Denoising by Integrating Super-Resolution


Abstract:

Light field, a promising representation to describe the scene appearance, is susceptible to various noise due to the current sensor design. This paper proposes a novel te...Show More

Abstract:

Light field, a promising representation to describe the scene appearance, is susceptible to various noise due to the current sensor design. This paper proposes a novel tensor-based denoising method for the 4D light field that consists of two main steps. First, we generalize the intrinsic tensor sparsity measure to light field images by exploiting the nonlocal similarity across the spatial and angular dimensions. Second, we further exploit the spatial-angular correlation by integrating light field super-resolution into the denoising process to eliminate the sub-pixel misalignment of different views. After a back-projection from the refined high-resolution central view under an intensity consistency criteria, the denoising performance for the light field can be boosted. Experimental results validate the superior performance of the proposed method in terms of both PSNR and visual quality on the HCI light field dataset.
Date of Conference: 07-10 October 2018
Date Added to IEEE Xplore: 06 September 2018
ISBN Information:
Electronic ISSN: 2381-8549
Conference Location: Athens, Greece

References

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