Dynamic range enhancement algorithms for CMOS sensors with non-destructive readout

Kachatkou, Anton; Silfhout, Roelof van

doi:10.1109/ist.2008.4659956

Cited by 4 publications

(9 citation statements)

References 12 publications

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“…Using a global maximum a posteriori optimization with priors that enforce correlation between color channels, Farsiu et al [37] proposed a framework for joint super-resolution and demosaicing. A similar approach was taken in [38] for HDR imaging with joint demosaicing for sensors with non-destructive readout (i.e. perfect alignment between consecutive readouts/frames).…”

Section: Demosaicingmentioning

confidence: 99%

A unified framework for multi-sensor HDR video reconstruction

Kronander

Gustavson

Bonnet³

et al. 2014

Signal Processing: Image Communication

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One of the most successful approaches to modern high quality HDR-video capture is to use camera setups with multiple sensors imaging the scene through a common optical system. However, such systems pose several challenges for HDR reconstruction algorithms. Previous reconstruction techniques have considered debayering, denoising, resampling (alignment) and exposure fusion as separate problems. In contrast, in this paper we present a unifying approach, performing HDR assembly directly from raw sensor data. Our framework includes a camera noise model adapted to HDR video and an algorithm for spatially adaptive HDR reconstruction based on fitting of local polynomial approximations to observed sensor data. The method is easy to implement and allows reconstruction to an arbitrary resolution and output mapping. We present an implementation in CUDA and show real-time performance for an experimental 4 Mpixel multi-sensor HDR video system. We further show that our algorithm has clear advantages over existing methods, both in terms of flexibility and reconstruction quality.

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Section: Demosaicingmentioning

confidence: 99%

A unified framework for multi-sensor HDR video reconstruction

Kronander

Gustavson

Bonnet³

et al. 2014

Signal Processing: Image Communication

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“…Since the 'up-the-ramp' reconstruction is a linear procedure and treats every pixel individually, no additional distortions are introduced. However, it has previously been shown [19] that a linear extrapolation of the saturated pixels' value suffers from 'stepped gradient' artefacts. They appear due to the amplification of the noise present in raw data.…”

Section: Hdr Colour Imaging Using Sequential Data Reconstructionmentioning

confidence: 99%

“…During subsequent demosaicing, these artefacts will be transferred to the full colour image and can create additional sources of colour errors. Therefore, in a sequential approach, it is important to address this problem separately, for example by applying a dedicated extrapolation algorithm to the results of 'up-the-ramp' reconstruction [19].…”

Section: Hdr Colour Imaging Using Sequential Data Reconstructionmentioning

confidence: 99%

“…The detailed description of the architecture of the camera is given in [18]. Below we analyse the colour reconstruction options available and propose a joint demosaicing and DR enhancement method which is a result of further development of the joint colour reconstruction algorithm originally suggested in [19]. We then compare the results of different algorithms for both synthetic and real images.…”

Section: Introductionmentioning

confidence: 99%

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High dynamic range colour imaging using complementary metal-oxide-semiconductor (CMOS) sensors with non-destructive readout

Kachatkou

Silfhout²

2009

Meas. Sci. Technol.

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We present a novel colour reconstruction approach for a high dynamic range camera based on a CMOS sensor with non-destructive readout. The output of such a sensor consists of a sequence of noisy mosaic images that can be combined to create a colour image having a high dynamic range. We show that intuitive sequential processing, where dynamic range enhancement is followed by conventional demosaicing, is prone to introduce extra errors due to ‘stepped gradient’ artefacts and residual system noise. We propose an alternative joint reconstruction algorithm that utilizes all available data to improve the quality of the resulting full colour image. Conventional colour reconstruction quality evaluation, camera noise tests and visual observations show that the proposed method does not produce ‘stepped gradient’ artefacts and generally outperforms a sequential approach based on traditional demosaicing routines for a wide range of system noise values. It also provides a steady increase in dynamic range when the number of non-destructive samples grows.

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“…Non-destructive readout (NDR) operates by sampling the signal many times during the integration time without affecting the built up photocharge. The CIS is read with up-the-ramp sampling, as widely used on IR photodiode arrays for DR increase [12] [13] and for cosmic ray rejection [14].…”

Section: Introductionmentioning

confidence: 99%

A Method to Achieve High Dynamic Range in a CMOS Image Sensor Using Interleaved Row Readout

et al. 2022

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We present a readout scheme for CMOS image sensors that can be used to achieve arbitrarily high dynamic range (HDR) in principle. The linear full well capacity (LFWC) in high signal regions was extended 50 times from 20 ke − to 984 ke − via an interlaced row-wise readout order, whilst the noise floor remained unchanged in low signal regions, resulting in a 34 dB increase in DR. The peak signal-to-noise ratio (PSNR) is increased in a continuous fashion from 43 dB to 60 dB. This was achieved by summing user-selected rows which were read out multiple times. Centroiding uncertainties were lowered when template-fitting a projected pattern, compared to the standard readout scheme. Example applications are aimed at scientific imaging due to the linearity and PSNR increase.

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Dynamic range enhancement algorithms for CMOS sensors with non-destructive readout

Cited by 4 publications

References 12 publications

A unified framework for multi-sensor HDR video reconstruction

A unified framework for multi-sensor HDR video reconstruction

High dynamic range colour imaging using complementary metal-oxide-semiconductor (CMOS) sensors with non-destructive readout

A Method to Achieve High Dynamic Range in a CMOS Image Sensor Using Interleaved Row Readout

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