Unbounded High Dynamic Range Photography Using a Modulo Camera

Zhao, Hang; Shi, Boxin; Fernandez-Cull, Christy; Yeung, Sai-Kit; Raskar, Ramesh

doi:10.1109/iccphot.2015.7168378

Cited by 75 publications

(77 citation statements)

References 24 publications

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“…However, the inherent assumption there is that the input image has very few sharp discontinuities, and this makes it unsuitable for practical situations with textured images. Our work is motivated by the recent work of [2] on high dynamic range (HDR) imaging using a modulo camera sensor. For image reconstruction using multiple measurements, they propose the multi-shot UHDR recovery algorithm, with follow-ups developed further in [30].…”

Section: Prior Workmentioning

confidence: 99%

Signal Reconstruction From Modulo Observations

Shah

Hegde

2019

2019 IEEE Global Conference on Signal and Information Processing (GlobalSIP)

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We consider the problem of reconstructing a signal from under-determined modulo observations (or measurements). This observation model is inspired by a (relatively) less wellknown imaging mechanism called modulo imaging, which can be used to extend the dynamic range of imaging systems; variations of this model have also been studied under the category of phase unwrapping. Signal reconstruction in the underdetermined regime with modulo observations is a challenging ill-posed problem, and existing reconstruction methods cannot be used directly. In this paper, we propose a novel approach to solving the inverse problem limited to two modulo periods, inspired by recent advances in algorithms for phase retrieval under sparsity constraints. We show that given a sufficient number of measurements, our algorithm perfectly recovers the underlying signal and provides improved performance over other existing algorithms. We also provide experiments validating our approach on both synthetic and real data to depict its superior performance.

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Section: Prior Workmentioning

confidence: 99%

Signal Reconstruction From Modulo Observations

Shah

Hegde

2019

2019 IEEE Global Conference on Signal and Information Processing (GlobalSIP)

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“…The modulo camera concept of Zhao et al . [22] aims to mitigate this using a novel, practical sensor that, instead of saturating, resets pixels to zero as soon as their maximal value is reached during the exposure. Hence, the least significant bits of the signal can be measured independently of its overall magnitude.…”

Section: Introductionmentioning

confidence: 99%

“…(a) 16-bit ground truth (b) Modulo camera reconstruction using [22] (c) Proposed modulo camera reconstruction (d) Conventional HDR reconstruction (saturating sensor) Fig. 1.…”

Section: Introductionmentioning

confidence: 99%

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Robust Multi-image HDR Reconstruction for the Modulo Camera

Läng

Plötz

Roth

2017

Lecture Notes in Computer Science

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Photographing scenes with high dynamic range (HDR) poses great challenges to consumer cameras with their limited sensor bit depth. To address this, Zhao et al. recently proposed a novel sensor concept -the modulo camera -which captures the least significant bits of the recorded scene instead of going into saturation. Similar to conventional pipelines, HDR images can be reconstructed from multiple exposures, but significantly fewer images are needed than with a typical saturating sensor. While the concept is appealing, we show that the original reconstruction approach assumes noise-free measurements and quickly breaks down otherwise. To address this, we propose a novel reconstruction algorithm that is robust to image noise and produces significantly fewer artifacts. We theoretically analyze correctness as well as limitations, and show that our approach significantly outperforms the baseline on real data.

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“…Here the derivative w.r.t. complex-valued variable are not straight forward and we adopt Wirtinger calculus [50] which is explained in (22). According to this framework, ∂ z k ∂ z k = 1 and ∂ z k ∂ z * k = 0.…”

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confidence: 99%

SURE-Fuse WFF: A Multi-Resolution Windowed Fourier Analysis for Interferometric Phase Denoising

2019

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Interferometric phase (InPhase) imaging is an important part of many present-day coherent imaging technologies. Often in such imaging techniques, the acquired images, known as interferograms, suffer from two major degradations: 1) phase wrapping caused by the fact that the sensing mechanism can only measure sinusoidal 2π-periodic functions of the actual phase, and 2) noise introduced by the acquisition process or the system. This work focusses on InPhase denoising which is a fundamental restoration step to many posterior applications of InPhase, namely to phase unwrapping. The presence of sharp fringes that arises from phase wrapping makes InPhase denoising a hard-inverse problem. Motivated by the fact that the InPhase images are often locally sparse in Fourier domain, we propose a multi-resolution windowed Fourier filtering (WFF) analysis that fuses WFF estimates with different resolutions, thus overcoming the WFF fixed resolution limitation. The proposed fusion relies on an unbiased estimate of the mean square error derived using the Stein's lemma adapted to complex-valued signals. This estimate, known as SURE, is minimized using an optimization framework to obtain the fusion weights. Strong experimental evidence, using synthetic and real (InSAR & MRI) data, that the developed algorithm, termed as SURE-fuse WFF, outperforms the best hand-tuned fixed resolution WFF as well as other state-of-the-art InPhase denoising algorithms, is provided.

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Unbounded High Dynamic Range Photography Using a Modulo Camera

Abstract: Abstract

Cited by 75 publications

References 24 publications

Signal Reconstruction From Modulo Observations

Signal Reconstruction From Modulo Observations

Robust Multi-image HDR Reconstruction for the Modulo Camera

SURE-Fuse WFF: A Multi-Resolution Windowed Fourier Analysis for Interferometric Phase Denoising

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