Dynamic Low-Light Imaging with Quanta Image Sensors

Chi, Yiheng; Gnanasambandam, Abhiram; Koltun, Vladlen; Chan, Stanley H.

doi:10.1007/978-3-030-58589-1_8

Cited by 34 publications

(24 citation statements)

References 54 publications

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“…Therefore, the number of detected photons per pixel within a certain time will differ even if the incident light intensity is constant. In measurements involving a small number of photons, such differences in photon incidence become a significant source of noise [7], which is referred to as "photon-shot-noise." This noise is also common in CMOS image sensors [7].…”

Section: B Image Reconstruction Of Bit-plane Framesmentioning

confidence: 99%

“…In measurements involving a small number of photons, such differences in photon incidence become a significant source of noise [7], which is referred to as "photon-shot-noise." This noise is also common in CMOS image sensors [7]. Efforts have been made to develop image reconstruction methods for acquiring high-quality multi-bit images from bitplane frames even in photon-limited situations.…”

Section: B Image Reconstruction Of Bit-plane Framesmentioning

confidence: 99%

“…The development of methods for obtaining high-quality images in photon-limited situations would be useful in several fields, including medicine, security, and science [1]- [4]. Relative to a complementary metal-oxide semiconductor (CMOS) image sensor, which has been generally used in recent years, imaging devices with single-photon detection sensitivity, such as single-photon avalanche diodes (SPAD) sensors [5] and quanta image sensors (QIS) [6], have significant advantages in terms of high sensitivity and temporal resolution under photon-limited imaging conditions [7], [8]. Such imaging devices could also be used for consumer imaging applications [9].…”

Section: Introductionmentioning

confidence: 99%

“…In such methods, increasing the number of bit-plane frames in the time direction generally enhances the quality of the reconstructed multi-bit image through an improvement in the image's signal-to-noise ratio (SNR) [10]. However, when moving objects are captured, motion blur is likely to occur on reconstructed images produced using large numbers of bit-plane frames [7]. This motion blur occurs because of the integration of many bit-plane frames with different positions corresponding to the object motion in each frame.…”

Section: Introductionmentioning

confidence: 99%

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Image Quality Improvements Based on Motion-Based Deblurring for Single-Photon Imaging

2021

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Photon counting imaging can be used to capture clearly photon-limited scenes. In photon counting imaging, information on incident photons is obtained as binary frames (bit-plane frames), which are transformed into a multi-bit image in the reconstruction process. In this process, it is necessary to apply a deblurring method to enable the capture of dynamic scenes without motion blur. In this paper, a deblurring method for the high-quality bit-plane frame reconstruction of dynamic scenes is proposed. The proposed method involves the deblurring of units of object motion within a scene through the application of motion compensation to pixels sharing the same motions. This method achieves more efficient motion blur suppression than the application of simple deblurring to pixel block or spatial region units. It also applies a novel technique for accurate motion estimation from the bit-plane frame even in photon-limited situations through the statistical evaluation of the temporal variation of photon incidence. In addition to deblurring, our experimental results also revealed that the proposed method can be applied for denoising, which improves the peak signal-to-noise ratio by 1.2 dB. In summary, the proposed method for bit-plane reconstruction achieves high quality imaging even in photon-limited dynamic scenes.

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Section: B Image Reconstruction Of Bit-plane Framesmentioning

confidence: 99%

Section: B Image Reconstruction Of Bit-plane Framesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Image Quality Improvements Based on Motion-Based Deblurring for Single-Photon Imaging

2021

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“…These factors have made QIS an excellent candidate for imaging dark and dynamic scenes. Recent reports in computer vision have proved the effectiveness of the sensors in various applications [4]- [7].…”

Section: Introductionmentioning

confidence: 99%

HDR Imaging With Quanta Image Sensors: Theoretical Limits and Optimal Reconstruction

Gnanasambandam

Chan

2020

IEEE Trans. Comput. Imaging

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High dynamic range (HDR) imaging is one of the biggest achievements in modern photography. Traditional solutions to HDR imaging are designed for and applied to CMOS image sensors (CIS). However, the mainstream onemicron CIS cameras today generally have a high read noise and low frame-rate. Consequently, these sensors have limited acquisition speed, making the cameras slow in the HDR mode. In this paper, we propose a new computational photography technique for HDR imaging. Recognizing the limitations of CIS, we use the Quanta Image Sensors (QIS) to trade spatial-temporal resolution with bit-depth. QIS are single-photon image sensors that have comparable pixel pitch to CIS but substantially lower dark current and read noise. We provide a complete theoretical characterization of the sensor in the context of HDR imaging, by proving the fundamental limits in the dynamic range that QIS can offer and its trade-offs with noise and speed. In addition, we derive an optimal reconstruction algorithm for single-bit and multi-bit QIS. Our algorithm is theoretically optimal for all linear reconstruction schemes based on exposure bracketing. Experimental results confirm the validity of the theory and algorithm, based on synthetic and real QIS data.

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Advanced Optical Imaging Technologies for Microplastics Identification: Progress and Challenges

Zhu,

Li,

Huang

et al. 2024

Advanced Photonics Research

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Global concern about microplastic (MP) and nanoplastic (NP) particles is continuously rising with their proliferation worldwide. Effective identification methods for MP and NP pollution monitoring are highly needed, but due to different requirements and technical challenges, much of the work is still in progress. Herein, the advanced optical imaging systems that are successfully applied or have the potential for MP identification are focused on. Compared with chemical and thermal analyses, optical methods have the unique advantages of being nondestructive and noncontact and allow fast detection without complex sample preprocessing. Furthermore, they are capable of revealing the morphology, anisotropy, and material characteristics of MP for their quick and robust detection. This review aims to present a comprehensive discussion of the relevant optical imaging systems, emphasizing their operating principles, strengths, and drawbacks. Multiple comparisons and analyses among these technologies are conducted in order to provide practical guidelines for researchers. In addition, the combination of optical and other alternative technologies is described and the representative portable MP detection devices are highlighted. Together, they shed light on the prospects for long‐term MP pollution monitoring and environmental protection.

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Dynamic Low-Light Imaging with Quanta Image Sensors

Cited by 34 publications

References 54 publications

Image Quality Improvements Based on Motion-Based Deblurring for Single-Photon Imaging

Image Quality Improvements Based on Motion-Based Deblurring for Single-Photon Imaging

HDR Imaging With Quanta Image Sensors: Theoretical Limits and Optimal Reconstruction

Advanced Optical Imaging Technologies for Microplastics Identification: Progress and Challenges

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