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Title: Guidance-based improved depth upsampling with better initial estimate

Authors: Chandra Shaker Balure; Ramesh Kini M

Addresses: Department of Electronics and Communication, National Institute of Technology Karnataka, Surathkal, India ' Department of Electronics and Communication, National Institute of Technology Karnataka, Surathkal, India

Abstract: Like optical images, depth images are also gaining popularity because of its use in many applications like robot navigation, augmented reality, 3DTV and more. The commercially available depth cameras generate depth images which suffer from low spatial resolution, corrupted with noise, and missing regions. Such images need to be super-resolved, denoised and inpainted before using them to have better accuracy. Super-resolution (SR) techniques can be used to produce a high-resolution output. Since SR is an ill-posed inverse problem, a good initial estimate is always a good regulariser to find the optimal solution. We propose an initial estimate as part of our SR pipeline, esp. ×8, which will helps in quick convergence and accurate output. We propose a cascade approach by combining residual interpolation (RI) method with anisotropic total generalised variation (ATGV) method, both uses HR guidance image. The improvements are shown qualitative and quantitative with different levels of noise.

Keywords: super-resolution; depth image; initial estimate; interpolation; cascade.

DOI: 10.1504/IJCVR.2021.111878

International Journal of Computational Vision and Robotics, 2021 Vol.11 No.1, pp.109 - 125

Accepted: 19 Aug 2019
Published online: 18 Nov 2020 *

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