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Proceedings ArticleDOI

Depth from Diffusion

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TLDR
A novel depth estimation method that places a diffuser in the scene prior to image capture that is analogous to conventional depth-from-defocus (DFD), where the scatter angle of the diffuser determines the effective aperture of the system.
Abstract
An optical diffuser is an element that scatters light and is commonly used to soften or shape illumination. In this paper, we propose a novel depth estimation method that places a diffuser in the scene prior to image capture. We call this approach depth-from-diffusion (DFDiff). We show that DFDiff is analogous to conventional depth-from-defocus (DFD), where the scatter angle of the diffuser determines the effective aperture of the system. The main benefit of DFDiff is that while DFD requires very large apertures to improve depth sensitivity, DFDiff only requires an increase in the diffusion angle – a much less expensive proposition. We perform a detailed analysis of the image formation properties of a DFDiff system, and show a variety of examples demonstrating greater precision in depth estimation when using DFDiff.

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Citations
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Defocus map estimation from a single image

TL;DR: This paper presents a simple yet effective approach to estimate the amount of spatially varying defocus blur at edge locations, and demonstrates the effectiveness of this method in providing a reliable estimation of the defocus map.
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Computational Cameras: Convergence of Optics and Processing

TL;DR: This paper uses the abstract notion of light field representation as a general tool to describe computational camera designs, where each camera can be formulated as a projection of a high-dimensional light field to a 2-D image sensor.
Proceedings ArticleDOI

Depth Recovery from Light Field Using Focal Stack Symmetry

TL;DR: A technique to recover depth from a light field (LF) using two proposed features of the LF focal stack, one of which is the property that non-occluding pixels exhibit symmetry along the focal depth dimension centered at the in-focus slice.
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Spatially-Varying Blur Detection Based on Multiscale Fused and Sorted Transform Coefficients of Gradient Magnitudes

TL;DR: In this paper, a high-frequency multiscale fusion and sort transform (HiFST) of gradient magnitudes was proposed to detect spatially-varying blur.
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When Does Computational Imaging Improve Performance

TL;DR: The results show that computational imaging techniques do not provide a significant performance advantage when imaging with illumination that is brighter than typical daylight, and can be readily used by practitioners to design the most suitable imaging systems given the application at hand.
References
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Book

The scattering of electromagnetic waves from rough surfaces

TL;DR: The scattering of electromagnetic waves from rough surfaces PDF is available at the online library of the University of Southern California as mentioned in this paper, where a complete collection of electromagnetic wave from rough surface books can be found.
Proceedings ArticleDOI

Image and depth from a conventional camera with a coded aperture

TL;DR: A simple modification to a conventional camera is proposed to insert a patterned occluder within the aperture of the camera lens, creating a coded aperture, and introduces a criterion for depth discriminability which is used to design the preferred aperture pattern.
Journal ArticleDOI

Structure from stereo-a review

TL;DR: Broad categories of stereo algorithms are identified on the basis of differences in imaging geometry, matching primitives, and the computational structure used for the extraction of the 3D structure of a scene.
Book

A new sense for depth of field

Alex Pentland
TL;DR: In this paper, the authors examined a novel source of depth information: focal gradients resulting from the limited depth of field inherent in most optical systems and proved that this source of information can be used to make reliable depth maps of useful accuracy with relatively minimal computation.
Journal ArticleDOI

Computational Stereo

TL;DR: The criteria that are important for evaluating the effectiveness of various computational stereo techniques are presented and a representative sampling of computational stereo research is provided.
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