Adaptive-integration-time image sensor with real-time reconstruction function

Yasuda, T.; Hamamoto, Takayuki; Aizawa, Kiyoharu

doi:10.1109/ted.2002.806959

Cited by 32 publications

(10 citation statements)

References 4 publications

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“…This thesis describes a variant of the predictive multiple sampling method which improves, expands and systematizes efforts previously reported [52][53][54]. …”

mentioning

confidence: 85%

Predictive Multiple Sampling Algorithm With Overlapping Integration Intervals for Linear Wide Dynamic Range Integrating Image Sensors

Acosta-Serafini

Masaki

Sodini

2004

IEEE Trans. Intell. Transport. Syst.

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Machine vision systems are used in a wide range of applications such as security, automated quality control and intelligent transportation systems. Several of these systems need to extract information from natural scenes in the section of the electromagnetic spectrum visible to humans. These scenes can easily have intra-frame illumination ratios in excess of 10 6 : 1. Solid-state image sensors that can correctly process wide illumination dynamic range scenes are therefore required to to ensure correct reliability and performance.This thesis describes a new algorithm to linearly increase the illumination dynamic range range of integrating-type image sensors. A user-defined integration time is taken as a reference to create a potentially large set of integration intervals of different duration (the selected integration time being the longest) but with a common end. The light intensity received by each pixel in the sensing array is used to choose the optimal integration interval from the set, while a pixel saturation predictive decision is used to overlap the integration intervals within the given integration time such that only one frame using the optimal integration interval for each pixel is produced. The total integration time is never exceeded. Benefits from this approach are motion minimization, real-time operation, reduced memory requirements, programmable light intensity dynamic range increase and access to incremental light intensity information during the integration time. The algorithm is fully described with special attention to the resulting sensor transfer function, the signal-to-noise ratio, characterization of types and effects of errors in the predictive decision, calculation of the optimal integration intervals set given a certain set size, calculation of the optimal number of integration intervals, and impact of the new algorithm to image data compression.An efficient mapping of this algorithm to a CMOS process was done by designing a proof-of-concept integrated circuit in a 0.18µm 1.8V 5-metal layer process. The major components of the chip are a 1/3" VGA (640 × 480) pixel array, a 4bit per pixel memory array, an integration controller array and an analog-to-digital converter/correlated double sampled (ADC/CDS) array. Supporting components include pixel and memory row decoders, memory and converter output digital multiplexers, pixel-to-ADC/CDS analog multiplexer and test structures. The pixels have a fill factor of nearly 50%, as most of the needed system additions and complexity were taken off-pixel. The prototype is fully functional and linearly expands the dynamic range by more than 60dB.

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“…This thesis describes a variant of the predictive multiple sampling method which improves, expands and systematizes efforts previously reported [52][53][54]. …”

mentioning

confidence: 85%

Predictive Multiple Sampling Algorithm With Overlapping Integration Intervals for Linear Wide Dynamic Range Integrating Image Sensors

Acosta-Serafini

Masaki

Sodini

2004

IEEE Trans. Intell. Transport. Syst.

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“…In a CMOS image sensor, a variety of techniques can be used. These include combining multiple images having different exposure times [4], installing a logarithmic conversion circuit in each pixel [5], [6], adjusting pixel exposure time by conditional resets [7], switching between pixel circuit configurations [8], and changing saturation characteristics by modulating PD capacitance to [9]. In this paper, we show how to achieve a wide-dynamic-range by using negative-feedback resets to modulate the PD capacitance of each pixel individually.…”

Section: A Dealing With Optical Intensitymentioning

confidence: 99%

A Wide-Dynamic-Range Compression Image Sensor With Negative-Feedback Resetting

Ikebe

Saito

2007

IEEE Sensors J.

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“…The dynamic range of standard CMOS imagers, defined as the ratio of the maximum and minimum detectable illumination levels, is low (60 dB) compared to the dynamic range of a typical scene (120 dB). In the last 6 years, several different architectures for CMOS image sensor with wide dynamic range were proposed [7][8][9][10][11][12]. An attractive approach is using the digital pixel sensor (DPS) architecture in which an eight bit analog to digital converter and memory are integrated in the pixel [13].…”

Section: Introductionmentioning

confidence: 99%

A multisampling time-domain CMOS imager with synchronous readout circuit

Campos

Marinov

Faramarzpour

et al. 2008

Analog Integr Circ Sig Process

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A novel multisampling time-domain architecture for CMOS imagers with synchronous readout and wide dynamic range is proposed. The proposed multisampling architecture requires only a single bit per pixel memory instead of 8 bits which is typical for time-domain active pixel architectures. The goal is to obtain a time-domain imager with high dynamic range that requires lower number of transistors per pixel in order to achieve higher fill-factor. The maximum frame rate is analyzed as a function of number of bits and array size. The analysis shows that it is possible to achieve high frame rates and operate in video mode having 10 bit pixel data resolution. Also, we present analysis of the impact of comparator offset voltage on the fixed pattern noise. The architecture was implemented in an imager prototype with 32 9 32 pixel array fabricated in AMS CMOS 0.35 lm and was characterized for sensitivity, noise and color response. The pixel size is 30 lm 9 26 lm and it is composed of an n+/psub photodiode, a comparator and a D flip-flop with a 16% fill-factor.

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Adaptive-integration-time image sensor with real-time reconstruction function

Cited by 32 publications

References 4 publications

Predictive Multiple Sampling Algorithm With Overlapping Integration Intervals for Linear Wide Dynamic Range Integrating Image Sensors

Predictive Multiple Sampling Algorithm With Overlapping Integration Intervals for Linear Wide Dynamic Range Integrating Image Sensors

A Wide-Dynamic-Range Compression Image Sensor With Negative-Feedback Resetting

A multisampling time-domain CMOS imager with synchronous readout circuit

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