Transfer efficiency and depth invariance in computational cameras

Baek, Jiwon

doi:10.1109/iccphot.2010.5585098

Cited by 10 publications

(17 citation statements)

References 25 publications

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“…6(b), the MTF is oscillating, reaching maxima at s = n∆s and minima at s = (n+1/2)∆s for integer n (Table II(a) shows n = 0 case). The oscillation amplitude becomes larger for higher frequencies, which was also observed in [Baek 2010], meaning that MTF invariance is low. The average MTF is shown to be around…”

Section: Mtf Invariance Integration Surface Integration Windowsupporting

confidence: 51%

“…This paper builds upon the previous analyses of computational cameras in relation to light field capture and rendering [Ng 2005;Levin and Durand 2010], depth of field extension Hasinoff et al 2009a;Baek 2010] and motion deblurring Cho et al 2010;Bando et al 2011].…”

Section: Theoretical Analysesmentioning

confidence: 99%

“…(4), and it also attenuates image high frequencies. In this paper we are more interested in invariant capture, but pursuing PSF invariance alone could degrade deblurring performance, as there is a trade-off between PSF invariance and high frequency preservation [Baek 2010] (e.g., narrow-aperture shortexposure capture is a trivial solution to minimizing PSF variance by sacrificing high frequency preservation). Hence, we would like to choose kernel k that minimizes PSF variance while maximizing high frequency preservation for a range of depth and motion.…”

Section: Psf Invariance and High Frequency Preservationmentioning

confidence: 99%

“…4.2. We have considered using more elaborate measures such as [Baek 2010] by extending them to motion-invariance, but resultant complicated equations hindered tractable analysis of all of the existing camera designs.…”

Section: Measure Of Psf Invariancementioning

confidence: 99%

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Near-invariant blur for depth and 2D motion via time-varying light field analysis

2013

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Recently, several camera designs have been proposed for either making defocus blur invariant to scene depth or making motion blur invariant to object motion. The benefit of such invariant capture is that no depth or motion estimation is required to remove the resultant spatially uniform blur. So far, the techniques have been studied separately for defocus and motion blur, and object motion has been assumed to be 1D (e.g., horizontal). This paper explores a more general capture method that makes both defocus blur and motion blur nearly invariant to scene depth and in-plane 2D object motion. We formulate the problem as capturing a time-varying light field through a time-varying light field modulator at the lens aperture, and perform 5D (4D light field + 1D time) analysis of all the existing computational cameras for defocus/motion-only deblurring and their hybrids. This leads to a surprising conclusion that focus sweep, previously known as a depth-invariant capture method that moves the plane of focus through a range of scene depth during exposure, is near-optimal both in terms of depth and 2D motion-invariance and in terms of high frequency preservation for certain combinations of depth and motion ranges. Using our prototype camera, we demonstrate joint defocus and motion deblurring for moving scenes with depth variation.

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Section: Mtf Invariance Integration Surface Integration Windowsupporting

confidence: 51%

Section: Theoretical Analysesmentioning

confidence: 99%

Section: Psf Invariance and High Frequency Preservationmentioning

confidence: 99%

Section: Measure Of Psf Invariancementioning

confidence: 99%

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Near-invariant blur for depth and 2D motion via time-varying light field analysis

2013

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“…Recently, Baek compared the degree of depth-invariance of these two techniques, and observed that focal sweep gives a near-optimal tradeoff between MTF and depth-invariance at all frequencies [Baek 2010], while wavefront coding is only guaranteed to be optimal at a single frequency. We introduce a new diffusion coding camera that produces near identical performance to focal sweep, but without the need for moving parts (see Figures 1,[15][16][17].…”

Section: Introductionmentioning

confidence: 99%

Diffusion coded photography for extended depth of field

Cossairt¹,

Zhou²,

Nayar³

2010

ACM SIGGRAPH 2010 Papers

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In recent years, several cameras have been introduced which extend depth of field (DOF) by producing a depth-invariant point spread function (PSF). These cameras extend DOF by deblurring a captured image with a single spatially-invariant PSF. For these cameras, the quality of recovered images depends both on the magnitude of the PSF spectrum (MTF) of the camera, and the similarity between PSFs at different depths. While researchers have compared the MTFs of different extended DOF cameras, relatively little attention has been paid to evaluating their depth invariances. In this paper, we compare the depth invariance of several cameras, and introduce a new diffusion coding camera that achieves near identical performance to a focal sweep camera, but without the need for moving parts.Our technique utilizes a novel optical element placed in the pupil plane of an imaging system. Whereas previous approaches use optical elements characterized by their amplitude or phase profile, our approach utilizes one whose behavior is characterized by its scattering properties. Such an element is commonly referred to as an optical diffuser, and thus we refer to our new approach as diffusion coding. We show that diffusion coding can be analyzed in a simple and intuitive way by modeling the effect of a diffuser as a kernel in light field space. We provide detailed analysis of diffusion coded cameras and show results from an implementation using a custom designed diffuser.

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An Analysis of Focus Sweep for Improved 2D Motion Invariance

Bandô

2013

2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops

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Transfer efficiency and depth invariance in computational cameras

Abstract: Abstract

Cited by 10 publications

References 25 publications

Near-invariant blur for depth and 2D motion via time-varying light field analysis

Near-invariant blur for depth and 2D motion via time-varying light field analysis

Diffusion coded photography for extended depth of field

An Analysis of Focus Sweep for Improved 2D Motion Invariance

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