Images from Bits: Non-Iterative Image Reconstruction for Quanta Image Sensors

Chan, Stanley H.; Elgendy, Omar A.; Wang, Xiran

doi:10.3390/s16111961

Cited by 52 publications

(44 citation statements)

References 48 publications

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“…We can also use learning-based methods, e.g., [26][27][28][29] to reconstruct the signal. The method we present here is based on the transform-denoise approach by Chan et al [10]. We prefer transform-denoise because it is a physics-based approach and is robust to different sensor configurations.…”

Section: Qis Color Image Reconstructionmentioning

confidence: 99%

Megapixel photon-counting color imaging using quanta image sensor

Gnanasambandam

Elgendy²,

Ma³

et al. 2019

Opt. Express

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Quanta Image Sensor (QIS) is a single-photon detector designed for extremely low light imaging conditions. Majority of the existing QIS prototypes are monochrome based on single-photon avalanche diodes (SPAD). Passive color imaging has not been demonstrated with single-photon detectors due to the intrinsic difficulty of shrinking the pixel size and increasing the spatial resolution while maintaining acceptable intra-pixel cross-talk. In this paper, we present image reconstruction of the first color QIS with a resolution of 1024×1024 pixels, supporting both single-bit and multi-bit photon counting capability. Our color image reconstruction is enabled by a customized joint demosaicing-denoising algorithm, leveraging truncated Poisson statistics and variance stabilizing transforms. Experimental results of the new sensor and algorithm demonstrate superior color imaging performance for very low-light conditions with a mean exposure of as low as a few photons per pixel in both real and simulated images.

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Section: Qis Color Image Reconstructionmentioning

confidence: 99%

Megapixel photon-counting color imaging using quanta image sensor

Gnanasambandam

Elgendy²,

Ma³

et al. 2019

Opt. Express

Self Cite

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“…Previously, in the context of time-correlated SPAD imaging, regularization-based approaches have been developed to reconstruct scene reflectivity [3], [9]. For oversampled binary observations, image reconstruction algorithms such as [10] are applicable. In this paper, our objective is to jointly recover spatial and temporal variations of radiance in dynamic scenes without spatial oversampling.…”

Section: Introductionmentioning

confidence: 99%

A Bit Too Much? High Speed Imaging from Sparse Photon Counts

Chandramouli¹,

Burri

Bruschini

et al. 2019

2019 IEEE International Conference on Computational Photography (ICCP)

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Recent advances in photographic sensing technologies have made it possible to achieve light detection in terms of a single photon. Photon counting sensors are being increasingly used in many diverse applications. We address the problem of jointly recovering spatial and temporal scene radiance from very few photon counts. Our ConvNet-based scheme effectively combines spatial and temporal information present in measurements to reduce noise. We demonstrate that using our method one can acquire videos at a high frame rate and still achieve good quality signal-to-noise ratio. Experiments show that the proposed scheme performs quite well in different challenging scenarios while the existing approaches are unable to handle them.

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“…Intensity reconstruction using the QIS approach has been developed using oversampled binary frames [20][21][22][23]. Based on an active imaging scheme capable of time-gated viewing [24], we report a single-photon depth profiling system using an advanced time-gated, high fill-factor (61%) SPAD image sensor with binary frame response at a high frame rate (up to 100 kfps) [25].…”

Section: Introductionmentioning

confidence: 99%

High-resolution depth profiling using a range-gated CMOS SPAD quanta image sensor

Ren¹,

Connolly²,

Halimi³

et al. 2018

Opt. Express

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A CMOS single-photon avalanche diode (SPAD) quanta image sensor is used to reconstruct depth and intensity profiles when operating in a range-gated mode used in conjunction with pulsed laser illumination. By designing the CMOS SPAD array to acquire photons within a pre-determined temporal gate, the need for timing circuitry was avoided and it was therefore possible to have an enhanced fill factor (61% in this case) and a frame rate (100,000 frames per second) that is more difficult to achieve in a SPAD array which uses time-correlated single-photon counting. When coupled with appropriate image reconstruction algorithms, millimeter resolution depth profiles were achieved by iterating through a sequence of temporal delay steps in synchronization with laser illumination pulses. For photon data with high signal-to-noise ratios, depth images with millimeter scale depth uncertainty can be estimated using a standard cross-correlation approach. To enhance the estimation of depth and intensity images in the sparse photon regime, we used a bespoke clustering-based image restoration strategy, taking into account the binomial statistics of the photon data and non-local spatial correlations within the scene. For sparse photon data with total exposure times of 75 ms or less, the bespoke algorithm can reconstruct depth images with millimeter scale depth uncertainty at a stand-off distance of approximately 2 meters. We demonstrate a new approach to single-photon depth and intensity profiling using different target scenes, taking full advantage of the high fill-factor, high frame rate and large array format of this range-gated CMOS SPAD array.

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Images from Bits: Non-Iterative Image Reconstruction for Quanta Image Sensors

Cited by 52 publications

References 48 publications

Megapixel photon-counting color imaging using quanta image sensor

Megapixel photon-counting color imaging using quanta image sensor

A Bit Too Much? High Speed Imaging from Sparse Photon Counts

High-resolution depth profiling using a range-gated CMOS SPAD quanta image sensor

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