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Journal ArticleDOI

Resolution Enhancement in Multi-Image Stereo

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TLDR
This paper proposes an integrated approach to estimate the HR depth and the SR image from multiple LR stereo observations and demonstrates the efficacy of the proposed method in not only being able to bring out image details but also in enhancing theHR depth over its LR counterpart.
Abstract
Under stereo settings, the twin problems of image superresolution (SR) and high-resolution (HR) depth estimation are intertwined. The subpixel registration information required for image superresolution is tightly coupled to the 3D structure. The effects of parallax and pixel averaging (inherent in the downsampling process) preclude a priori estimation of pixel motion for superresolution. These factors also compound the correspondence problem at low resolution (LR), which in turn affects the quality of the LR depth estimates. In this paper, we propose an integrated approach to estimate the HR depth and the SR image from multiple LR stereo observations. Our results demonstrate the efficacy of the proposed method in not only being able to bring out image details but also in enhancing the HR depth over its LR counterpart.

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Citations
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Journal ArticleDOI

A survey on super-resolution imaging

TL;DR: This paper provides a comprehensive review of SR image and video reconstruction methods developed in the literature and highlights the future research challenges.
Proceedings ArticleDOI

Learning Parallax Attention for Stereo Image Super-Resolution

TL;DR: A parallax-attention mechanism with a global receptive field along the epipolar line to handle different stereo images with large disparity variations is introduced and a new and the largest dataset for stereo image SR is proposed.
Patent

Glasses for viewing stereo images

TL;DR: In this paper, a set of spectacles are disclosed for use in viewing images or videos, and include at least two lenses each having an adjustable optical property and an image capture device associated with the spectacles for receiving a digital image comprising a plurality of digital image channels each containing multiple pixels.
Proceedings ArticleDOI

Enhancing the Spatial Resolution of Stereo Images Using a Parallax Prior

TL;DR: A novel method to learn a parallax prior from stereo image datasets by jointly training two-stage networks that enhances the spatial resolution of stereo images significantly more than single-image super-resolution methods.
Proceedings ArticleDOI

Flickr1024: A Large-Scale Dataset for Stereo Image Super-Resolution

TL;DR: Experimental results show that, as compared to the KITTI and Middlebury datasets, the Flickr1024 dataset can help to handle the over-fitting problem and significantly improves the performance of stereo SR methods.
References
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Journal ArticleDOI

Joint MAP registration and high-resolution image estimation using a sequence of undersampled images

TL;DR: A maximum a posteriori (MAP) framework for jointly estimating image registration parameters and the high-resolution image is presented and experimental results are provided to illustrate the performance of the proposed MAP algorithm using both visible and infrared images.
Book ChapterDOI

Multi-camera Scene Reconstruction via Graph Cuts

TL;DR: This paper addresses the problem of computing the 3-dimensional shape of an arbitrary scene from a set of images taken at known viewpoints by giving an energy minimization formulation of the multi-camera scene reconstruction problem.
Proceedings ArticleDOI

Optimizing Binary MRFs via Extended Roof Duality

TL;DR: An efficient implementation of the "probing" technique is discussed, which simplifies the MRF while preserving the global optimum, and a new technique which takes an arbitrary input labeling and tries to improve its energy is presented.
Proceedings ArticleDOI

Handling occlusions in dense multi-view stereo

TL;DR: Experimental results show a dramatic improvement using the first idea over conventional multibaseline stereo, especially when used in conjunction with a global energy minimization technique, and show that explicit occlusion labeling and visibility reasoning do help, but not significantly, if the spatial and temporal selection is applied first.
Proceedings ArticleDOI

Symmetric stereo matching for occlusion handling

TL;DR: This paper embeds the visibility constraint within an energy minimization framework, resulting in a symmetric stereo model that treats left and right images equally and can also incorporate segmentation as a soft constraint.
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