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Dynamic vision sensor (DVS) imaging quality is significantly affected by pixel noise and temporal contrast (TC), which is inversely proportional to sensitivity. To reduce the noise event rate and improve sensitivity in bright‐light conditions in the DVS pixel circuit, this paper proposes improvements to the conventional DVS pixel circuit. The proposed DVS pixel circuit adopts stacked medium‐threshold transistors instead of a single high‐threshold transistor in the photoreceptor and introduces a threshold switching circuit. Compared with the conventional DVS pixel circuit, this design increases event threshold normalized by root mean square (RMS) noise voltage, reducing the dim‐light noise bandwidth. Additionally, it achieves higher sensitivity in bright‐light conditions compared with dim‐light conditions. The proposed DVS pixel circuit is implemented in a 110‐nm complementary metal‐oxide semiconductor (CMOS) process. Post‐simulation results show that, for photocurrents between 5 fA and 100 pA, the proposed DVS pixel circuit achieves a 35 Hz peak event rate at 15% TC, which is reduced to 3.1% of the conventional structure. For photocurrents exceeding 30 pA, the proposed structure can switch TC from 15% to 5%, maintaining a noise event rate below 0.1 Hz. [ABSTRACT FROM AUTHOR]

To reduce the power consumption of a TDC in high-speed applications, a TDC architecture applied to SS ADC is proposed to reduce redundant counting. This structure can remove the identical part between two rows of pixel signals in a CMOS image sensor by adjusting the start and stop signal of the TDC, which will reduce the number of flipping of D flip-flops in the TDC. This structure requires the simultaneous readout of two rows of pixels in the high-speed CMOS image sensor. In the 110 nm CMOS process, simulation results show that the designed 5-bit TDC achieves an effective number of bits (ENOB) at 4.72 bits and a figure-of-merit (FOM) at 104.7–162.3 fJ/step, with a power consumption ranging from 60 µW to 93 µW. Compared with traditional counting methods, the proposed TDC can reduce counting power consumption by 30%. [ABSTRACT FROM AUTHOR]

In order to eliminate the noise on the pulse interval of high-speed spike-based image sensor, a pulse interval compensation (PIC) algorithm is proposed. Based on the analysis of the principle of sensor noise generation, a pulse interval error model is constructed and the compensation algorithm is developed. First, raw pulse data is obtained from the sensor system, and then the coefficient matrix is used to compensate the non-uniform pulse interval caused by the dark current. Then, the guided filter separates high-frequency noise from scenes details and the pulse interval compensation matrix is obtained in the corresponding pulse interval. Finally, the pulse interval compensation is performed on the raw pulse data for correction. In static scene experiments, the proposed method is compared with the existing state-of-the-art methods and shows a clear advantage in denoising in both low texture and rich texture scenes. In the experiment to film a turntable at a rotation speed of 2000 r/min, 3000 r/min, 6000 r/min, the average roughness decreases from 0.2830 to 0.2034, 0.2937 to 0.2139 and 0.3252 to 0.2501 respectively. These experiments proved that the proposed method can effectively eliminate the noise of the spike-based image sensor. [ABSTRACT FROM AUTHOR]

Active image sensors can only record scenes at low frame rates. The dynamic vision sensor (DVS) can capture high-speed scenes under challenging lighting conditions. However, DVS discards absolute light intensity information. The dynamic and active pixel vision image sensor (DAVIS) can output events and low-frame-rate grayscale images simultaneously. This paper proposes a high frame rate video reconstruction and deblurring algorithm based on events and low-speed blurred image sequences from DAVIS. First, we visualized events as a sequence of event images and performed image denoising process. Then, we used the extended 3D partial recursive search (E-3DPRS) method to generate high-performance motion vector field (MVF) between adjacent denoising event images with low computational complexity. MVF reflects the object motion trajectory with high time resolution. Furthermore, MVF is used as a priori information to restore potentially sharp images, which alleviates the highly ill-posed deblurring process. At last, we reconstructed a high frame rate sharp video based on a sharp image sequence and MVFs. Extensive experiments show that our proposed algorithm outperforms the existing state-of-the-art methods and achieves better average feature similarity and structural similarity. [ABSTRACT FROM AUTHOR]

This paper presents a leakage-suppressed capacitive-feedback amplifier (LSCFA) scheme for event-based vision sensors (EVS) to reduce the background event rate. Compared with the traditional capacitive-feedback amplifier (CFA) that employs power voltage as the reset voltage of the switch, the proposed LSCFA utilizes the output voltage in the reset state as the reset voltage of the switch. The proposed LSCFA is designed with a 22 nm 1P5M CMOS process. The post-simulation shows that the leakage current of the switch in LSCFA is 0.207 fA which is reduced by 89.8%, and the background event rate generated by the leakage current is 0.183 Hz which is reduced by 89.7%. The power dissipation of the EVS pixel with LSCFA is 488.7 nW which is increased by 8.8%. • Leakage current in event-based vision sensors is simulated and analyzed. • The pn junction leakage current and GIDL are dominant in the off state of a MOSFET. • The leakage current reaches the minimum value when V gs and V ds are near 0 V. • The proposed scheme employs output voltage in the reset state as the reset voltage. • The post-simulation shows the leakage current of the proposed scheme is suppressed. [ABSTRACT FROM AUTHOR]

A method of biomimetic visual perception and image reconstruction based on pulse sequence of events is proposed, and the proposed method facilitates a behavioral model of vision image sensing. Based on the model, the relationship between light condition and quality of reconstructed videos is analyzed. In this sensing method, pulse sequence is defined as synchronous pulse sequence. The sensing method adopts a synchronous pulse sequence readout and asynchronous pixel level sensing mechanism. Light intensity can be calculated by pulse sequences and image or video can be further reconstructed. As the photocurrent increases, the real-time performance of reconstructed image increases, but the depth of the reconstructed image decreases. Experiments are performed on sensing models with two types of pulse sequence generating methods. Method 1 adopts 1-bit data for each pixel, and Method 2 adopts 1-bit data accompanied by 3-bit time label which enables a lower frame rate. In the experiment with static images, the reconstructed images show better image depth under lower photocurrent. The mean square error (MSE) of the reconstructed image with 450 fA maximum photocurrent on Method 1 is 0.0737, whereas the MSE in the same condition on Method 2 is 0.0083. In the experiment with high-speed videos of 20000 f/s, the reconstructed videos with various photocurrents are evaluated by MSE analysis. When maximum photocurrent is between 6750 and 8250 fA as well as between 11250 and 16500 fA, the reconstructed high-speed videos have good MSE results, where video real-time and image depth are balanced. [ABSTRACT FROM AUTHOR]

This paper presents a modified pulse width modulation (PWM) readout method for DPS with block-based self-adjusted reference voltage to extend dynamic range (DR). In this scheme, pixel arrays are divided into blocks with the same size, and the exposure process consists of two periods. During the first exposure, block-based reference voltage is generated based on the average photocurrent within the block. In the second exposure, the generated voltage is used as the reference voltage for PWM readout. Then the quantization results are combined together to represent the luminance information. DR and peak signal-to-noise ratio (PSNR) were discussed with different images and integration time. Simulation results show that this scheme can achieve a DR of over 96dB with 8-bit memory and 8-bit ADC and 145dB with 12-bit memory and 12-bit ADC. It also has 28.98dB PSNR on average, better than 20.11dB in fixed reference voltage method and 17.25dB in ramp reference voltage method. Combining the feature of active pixel sensor (APS) and PWM readout, this scheme allows better DR but also obtains less distortion of the image reconstruction. [ABSTRACT FROM AUTHOR]

A pulse array image sensor (PAIS) is a bionic image sensor that converts light intensity into a pulse sequence to reduce the data volume. The traditional tracking method is not suitable for the sparse data form because of the absence of grayscale information. A trajectory tracking method based on a Bayesian classifier is proposed to maximize the property of the pulse data. First, candidate points with the smallest interval distances are selected in the area of interest. Then the total pulse numbers in a specified period at different positions are gathered to compose the positive and negative feature vectors, which are used to train a naive Bayesian classifier. The classifier can exactly obtain positions from the candidate points, and features in the new tracking positions train and update the classifier. The two-step filtering target point tracking algorithm using the interval distance and Bayesian classifier requires only the raw pulse data without processing, which can maximize the advantages of the special data format and improve computing efficiency. In this way, the position information can be directly obtained from pulse data, and the problem of wasting computing resources on reconstructing grayscale images and treating them in the traditional way is avoided. Experiments were performed on both real filmed data and the public event camera datasets. Our method can obtain trajectories with a high accuracy and long tracking time. The tracking errors are in single digits. In the comparison experiments, although our method has a smaller data volume than other models that obtain both frame and event data, the results still show that it has a comparable performance to the state-of-the-art methods. [ABSTRACT FROM AUTHOR]

A 128-stage CMOS time delay integration (TDI) image sensor with on-chip digital accumulator was presented in this paper. By using two sets of sampling capacitors and an optimized timing, the on-chip column parallel cyclic analog-to-digital converter (ADC) in the sensor conducts the correlated double sampling, digital program gain amplifying, and A/D conversion all altogether in one ADC’s conversion time simultaneously. An on-chip digital accumulator suitable for this sensor is also proposed. A prototype 1024 \times 128 CMOS TDI image sensor is fabricated in the 0.18- \mu \text{m} CMOS technology, and the measurement results proof that the pixels and readout circuits in the sensor work properly. With a line rate of 3875 lines/s, the sensor costs a power consumption of 290 mW and a silicon area of 18.2~\textrm {mm}\times 18.9$ mm. The estimated maximum sensitivity of the fabricated sensor is 2010 \textrm {V}/\textrm {lux}\cdot \textrm {sec} . This paper is suitable for applications in low-illumination, high scanning speed, and remote sensing systems. [ABSTRACT FROM PUBLISHER]

To improve the quality of reconstructed images of single-bit quanta image sensors, a self-adaptive threshold optimization method is proposed. The method can adaptively adjust the quantization threshold according to different light intensities, making the quality of the reconstructed image improved. First, the bitstream data from the quantization of real images are obtained by sensor model. Second, the optimal threshold value of each row is determined by calculating the bit-density, followed by the threshold value updated according to the deviation value between the bit-density of a single-pixel and 0.5. Finally, the optimal threshold matrix obtained by this method is used to reconstruct the image to improve imaging quality. Four identical test images were processed by the proposed method, the traditional method, and Elgendy's variable threshold method, respectively. The results show that the proposed method can improve the peak signal-to-noise ratio of the reconstructed image in comparison with the traditional uniform threshold method. Compared with Elgendy's method, the proposed method can effectively reduce the number of iterations under the same parameter conditions. These experiments prove that the proposed method can effectively improve the quality of reconstructed images with fewer iterations. [ABSTRACT FROM AUTHOR]

In the title paper, the temperature dependence of event threshold and leak activity frequency of dynamic vision sensor are researched, and a few new metrics are presented to describe the features of the leak event. A large amount of experimental data is shown to verify the theories. We comment on this paper, since Nozaki and Delbruck make some mistakes on formula derivation and the experimental data calculation. The errors are pointed out with detailed explanations, and the revised formulas and calculation results, together with some corresponding analyses, are provided. [ABSTRACT FROM AUTHOR]

In this paper, the non-ideal factors, which include spatial noise and temporal noise, are analyzed and suppressed in the high-speed spike-based image sensor, which combines the high-speed scanning sequential format with the method that uses the interspike time interval to indicate the scene information. In this imager, spatial noise contains device mismatch, which results in photo response non-uniformity (PRNU) and the non-uniformity of dark current. By multiplying the measured coefficient matrix the photo response non-uniformity is suppressed, and the non-uniformity of dark current is suppressed by correcting the interspike time interval based on the time interval of dark current. The temporal noise is composed of the shot noise and thermal noise. This kind of noise can be eliminated when using the spike frequency to restore the image. The experimental results show that, based on the spike frequency method, the standard deviation of the image decreases from 18.4792 to 0.5683 in the uniform bright light by using the calibration algorithm. While in the relatively uniform dark condition, the standard deviation decreases from 1.5812 to 0.4516. Based on interspike time interval method, because of time mismatch and temporal noise, the standard deviation of the image changes from 27.4252 to 27.4977 in the uniform bright light by using the calibration algorithm. While in the uniform dark condition, the standard deviation decreases from 2.361 to 0.3678. [ABSTRACT FROM AUTHOR]

This paper presents a low-power two-step double-data-rate (TS-DDR) counter without calibration for column-parallel single-slope analog-to-digital converter (SS ADC) in CMOS image sensor. A resolution alterable TS counting logic, which drives counting circuit to operate as a (N + M)-bit counter for the fine quantization and a M-bit MSB counter for the coarse quantization, is proposed to reduce the dynamic power consumption. As no calibration is required, the proposed counter is compatible with both digital correlated double sampling (D-CDS) and digital correlated multiple sampling (D-CMS). Moreover, a DDR structure without phase matching required for TS counter is employed to further reduce the power consumption. The proposed TS-DDR counter is implemented in 12-bit column-parallel SS ADCs for a CMOS image sensor. As a result, the proposed TS-DDR counter achieves a power consumption saving of at least 55.2% compared to a traditional one. The proposed SS ADC consumes 47.6 μW and has a DNL of +0.45/-0.55 LSB and an INL of +0.73/-2.36 LSB each column at 6.1 μs conversion time. [ABSTRACT FROM AUTHOR]

This paper focuses on a new non-ideal phenomenon induced by the power supply crosstalk (PSC) of the row drive circuit in 8 T global shutter (GS) CMOS image sensors (CISs). A method to eliminate the non-ideal phenomenon is presented. Based on the circuit simulation, the relationship between the parasitic resistance and PSC is analyzed. The PSC would cause a charge leakage on the sampling hold (S/H) capacitors in the 8 T pixel, which in turn attenuates the output signal of the image sensor. Through the mathematical model of the in-pixel S/H circuit, the effect of PSC and exposure on signal attenuation is analyzed. To eliminate signal attenuation, this paper utilizes a separate power layout method that isolates the row drivers in different columns by using multiple power supplies. In contrast to the method of sharing the power supply, the proposed method can reduce the maximum power supply crosstalk noise from 1.17 V to 2.58 μV in the 2000 × 2 row drive array. Based on the 0.13 μm CMOS process, the measurement results of the 1st chip design using the typical shared power structure and the 2nd chip design using the separate power supply structure are compared. The measurement results show that the output signal of the 1st chip design is limited to about 303 ADU due to the power supply crosstalk. The saturated output signal of the 2nd chip design is 2200 ADU, which is in accordance with the theoretical signal output value (2200 ADU) when the pixel is saturated. The proposed method can effectively eliminate signal attenuation induced by the PSC, thereby improving the image quality of 8 T GS CIS. [ABSTRACT FROM AUTHOR]