A Vision System With 1-inch 17-Mpixel 1000-fps Block-Controlled Coded-Exposure Stacked-CMOS Image Sensor for Computational Imaging and Adaptive Dynamic Range Control

Hirata, Tomoki; Murata, Hironobu; Arii, Taku; Matsuda, Hideaki; Yonemochi, Hajime; Tezuka, Y.; Tsunai, Shiro

doi:10.1109/ojcas.2022.3213062

Cited by 4 publications

(3 citation statements)

References 19 publications

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“…[101] In 2022, Hirata et al designed a back-illuminated stacked sensor to achieve a frame rate of 1000 fps and a resolution of 4k×4k. [102] Although the form of 3D stacking reduces the data transmission distance and improves the transmission bandwidth to a large extent, there is still the problem of transport limitation of bandwidth, i.e., the "transport wall" due to the lack of essential innovations in the architecture, and the solution of 3D stacking also brings troubles to the manufacturing process.…”

Section: Sensor Pre-processing Structurementioning

confidence: 99%

Advances in neuromorphic computing: Expanding horizons for AI development through novel artificial neurons and in-sensor computing

Yang 杨,

Zhao 赵,

Liu 刘

et al. 2024

Chinese Phys. B

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AI development has brought great success to upgrading the information age. At the same time, the large-scale Artificial Neural Network for building AI systems is thirsty for computing power, which is barely satisfied by the conventional computing hardware. In the post-Moore era, the increase in computing power brought about by the size reduction of CMOS in very large-scale integrated circuits (VLSIC) is challenging to meet the growing demand for AI computing power. To address the issue, technical approaches like neuromorphic computing attract great attention because of their feature of breaking Von-Neumann architecture, and dealing with AI algorithms much more parallelly and energy efficiently. Inspired by the human neural network architecture, neuromorphic computing hardware is brought to life based on novel artificial neurons constructed by new materials or devices. Although it is relatively difficult to deploy a training process in the neuromorphic architecture like spiking neural network (SNN), the development in this field has incubated promising technologies like in-sensor computing, which brings new opportunities for multidisciplinary research, including the field of optoelectronic materials and devices, artificial neural networks, and microelectronics integration technology. The vision chips based on the architectures could reduce unnecessary data transfer and realize fast and energy-efficient visual cognitive processing. This paper reviews firstly the architectures and algorithms of SNN, and artificial neuron devices supporting neuromorphic computing, then the recent progress of in-sensor computing vision chips, which all will promote the development of AI.

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Section: Sensor Pre-processing Structurementioning

confidence: 99%

Advances in neuromorphic computing: Expanding horizons for AI development through novel artificial neurons and in-sensor computing

Yang 杨,

Zhao 赵,

Liu 刘

et al. 2024

Chinese Phys. B

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“…Designing and developing detectors that can record a wide range of brightness variations is the ultimate solution for improving the dynamic range of imaging equipment. In this regard, Varnava C et al [3][4][5] have done a lot of excellent work. However, it will take some more time for this technical route to mature and practical as its high cost, low image resolution and effects.…”

Section: Introductionmentioning

confidence: 99%

Snapshot high dynamic range imaging based on adjustable attenuation microarray mask

Yang,

Ma,

Ning

et al. 2024

Sixth Conference on Frontiers in Optical Imaging and Technology: Novel Technologies in Optical Systems

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High Dynamic Range Imaging Based on Attenuation Microarray Mask has broad application prospects due to its good real-time performance and small size. But at the current level of craftsmanship, it is hard to fabricate a microattenuation array mask whose attenuation rate is adjustable. This leads to the fact that the imaging dynamic range cannot adapt to changes in scene brightness in most cases. To this end, this paper proposes a novel imaging system whose dynamic range can adaptively change according to the brightness of the scene. The core components are the micro polarization array mask mounted on the CMOS surface and the on-sensor rotatable linear polarizer in front of the lens. By controlling the rotation angle of the polarizer placed before the lens, the CMOS pixel exposure can be precisely controlled. Therefore, the imaging system dynamic range can be adjusted adaptively according to the scene brightness. Through horizontal comparison with Sony’s multi-quadrant polarization chip, we determined the optimal parameters of the multi-quadrant micro-polarization array mask for extending the dynamic range. The experimental results show that the imaging performance remains consistently good even when the dynamic range of the photographed scene is large, and the dynamic range of the device can be adapted to the dynamic range of the shooting scene, so that the image after shooting and processing can always show sufficient details. By rotating the polarizer in front of the lens to a specific angle, the high dynamic imaging of the scene can be significantly improved.

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Section: Introductionmentioning

confidence: 99%

Snapshot High Dynamic Range Imaging Based on Adjustable Attenuation Microarray Mask

Wenwenjing¹,

Cao²,

Zhao³

et al. 2023

Preprint

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High Dynamic Range Imaging Based on Attenuation Microarray Mask has broad application prospects due to its good real-time performance and small size. But at the current level of craftsmanship, it is hard to fabricate a micro-attenuation array mask whose attenuation rate is adjustable. This leads to the fact that the imaging dynamic range cannot adapt to changes in scene brightness in most cases. To this end, this paper proposes a novel imaging system where the dynamic range can be adaptively changed according to the brightness of the scene. The core components are the micro polarization array mask mounted on the CMOS surface and the on-sensor rotatable linear polarizer in front of the lens. By controlling the rotation angle of the polarizer placed before the lens, the CMOS pixel exposure can be precisely controlled. Therefore, the imaging system dynamic range can be adjusted adaptively according to the scene brightness. The experimental results show that the imaging performance remains consistently good even when the dynamic range of the scene is large. By rotating the polarizer in front of the lens to a specific angle, the high dynamic imaging of the scene can be significantly improved.

show abstract

A Vision System With 1-inch 17-Mpixel 1000-fps Block-Controlled Coded-Exposure Stacked-CMOS Image Sensor for Computational Imaging and Adaptive Dynamic Range Control

Cited by 4 publications

References 19 publications

Advances in neuromorphic computing: Expanding horizons for AI development through novel artificial neurons and in-sensor computing

Advances in neuromorphic computing: Expanding horizons for AI development through novel artificial neurons and in-sensor computing

Snapshot high dynamic range imaging based on adjustable attenuation microarray mask

Snapshot High Dynamic Range Imaging Based on Adjustable Attenuation Microarray Mask

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