scholarly journals The Analysis and Suppressing of Non-Uniformity in a High-Speed Spike-Based Image Sensor

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4232 ◽  
Author(s):  
Jing Gao ◽  
Yanzhao Wang ◽  
Kaiming Nie ◽  
Zhiyuan Gao ◽  
Jiangtao Xu
Keyword(s):  
Standard Deviation ◽  
Dark Current ◽  
High Speed ◽  
Bright Light ◽  
Image Sensor ◽  
Time Interval ◽  
Temporal Noise ◽  
Spatial Noise ◽  
Calibration Algorithm ◽  
Photo Response

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.

Extended noise equalisation for image compression in microscopical applications

2019 ◽  
Vol 86 (7-8) ◽  
pp. 422-432
Author(s):  
Daniel M. Kirchhöfer ◽  
Gerhard A. Holst ◽  
Fred S. Wouters ◽  
Stephan Hock ◽  
Bernd Jähne
Keyword(s):  
Machine Vision ◽  
Image Compression ◽  
Image Sensor ◽  
Image Noise ◽  
Noise Variance ◽  
Linear Amplification ◽  
Temporal Noise ◽  
Camera Systems ◽  
Illumination System ◽  
Photo Response

AbstractToday’s camera systems used for machine vision and scientific applications have intra-scene dynamic ranges up to 16 bit and therefore A/D converters with up to 16 bit resolution per pixel. Unfortunately, the linear amplification of electrons also forces a linear or even quadratic increase of the image noise variance with the signal. Based on a method published in 2016 (B. Jähne, M. Schwarzbauer, tm-Technisches Messen 83.1), this paper describes a more general nonlinear transformation which equalizes the combined effect of temporal noise and photo-response non-uniformity (PRNU) and/or temporal noise in the illumination system of an image sensor. With this generalisation it is possible to use the equalisation also for microscopic applications for which an example is discussed.

scholarly journals Neuro-Inspired Computing with Spin-VCSELs

2021 ◽  
Vol 11 (9) ◽  
pp. 4232
Author(s):  
Krishan Harkhoe ◽  
Guy Verschaffelt ◽  
Guy Van der Sande
Keyword(s):  
Processing Speed ◽  
Delay Time ◽  
High Speed ◽  
State Of The Art ◽  
Polarization Modulation ◽  
Time Interval ◽  
Computing Technique ◽  
High Modulation ◽  
Short Time ◽  
Modulation Speed

Delay-based reservoir computing (RC), a neuromorphic computing technique, has gathered lots of interest, as it promises compact and high-speed RC implementations. To further boost the computing speeds, we introduce and study an RC setup based on spin-VCSELs, thereby exploiting the high polarization modulation speed inherent to these lasers. Based on numerical simulations, we benchmarked this setup against state-of-the-art delay-based RC systems and its parameter space was analyzed for optimal performance. The high modulation speed enabled us to have more virtual nodes in a shorter time interval. However, we found that at these short time scales, the delay time and feedback rate heavily influence the nonlinear dynamics. Therefore, and contrary to other laser-based RC systems, the delay time has to be optimized in order to obtain good RC performances. We achieved state-of-the-art performances on a benchmark timeseries prediction task. This spin-VCSEL-based RC system shows a ten-fold improvement in processing speed, which can further be enhanced in a straightforward way by increasing the birefringence of the VCSEL chip.

scholarly journals Towards an Efficient CNN Inference Architecture Enabling In-Sensor Processing

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 1955
Author(s):  
Md Jubaer Hossain Pantho ◽  
Pankaj Bhowmik ◽  
Christophe Bobda
Keyword(s):  
Power Consumption ◽  
High Speed ◽  
Image Sensor ◽  
Machine Learning Algorithms ◽  
Hierarchical Optimization ◽  
Computation Method ◽  
Optimization Approach ◽  
Efficient Computation ◽  
Feature Maps ◽  
Dynamic Power

The astounding development of optical sensing imaging technology, coupled with the impressive improvements in machine learning algorithms, has increased our ability to understand and extract information from scenic events. In most cases, Convolution neural networks (CNNs) are largely adopted to infer knowledge due to their surprising success in automation, surveillance, and many other application domains. However, the convolution operations’ overwhelming computation demand has somewhat limited their use in remote sensing edge devices. In these platforms, real-time processing remains a challenging task due to the tight constraints on resources and power. Here, the transfer and processing of non-relevant image pixels act as a bottleneck on the entire system. It is possible to overcome this bottleneck by exploiting the high bandwidth available at the sensor interface by designing a CNN inference architecture near the sensor. This paper presents an attention-based pixel processing architecture to facilitate the CNN inference near the image sensor. We propose an efficient computation method to reduce the dynamic power by decreasing the overall computation of the convolution operations. The proposed method reduces redundancies by using a hierarchical optimization approach. The approach minimizes power consumption for convolution operations by exploiting the Spatio-temporal redundancies found in the incoming feature maps and performs computations only on selected regions based on their relevance score. The proposed design addresses problems related to the mapping of computations onto an array of processing elements (PEs) and introduces a suitable network structure for communication. The PEs are highly optimized to provide low latency and power for CNN applications. While designing the model, we exploit the concepts of biological vision systems to reduce computation and energy. We prototype the model in a Virtex UltraScale+ FPGA and implement it in Application Specific Integrated Circuit (ASIC) using the TSMC 90nm technology library. The results suggest that the proposed architecture significantly reduces dynamic power consumption and achieves high-speed up surpassing existing embedded processors’ computational capabilities.

scholarly journals On-CMOS Image Sensor Processing for Lane Detection

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3713
Author(s):  
Soyeon Lee ◽  
Bohyeok Jeong ◽  
Keunyeol Park ◽  
Minkyu Song ◽  
Soo Youn Kim
Keyword(s):  
Edge Detection ◽  
High Speed ◽  
Cmos Image Sensor ◽  
Image Sensor ◽  
Image Resolution ◽  
Lane Detection ◽  
Frame Rate ◽  
Total Power ◽  
Detection Accuracy ◽  
Total Power Consumption

This paper presents a CMOS image sensor (CIS) with built-in lane detection computing circuits for automotive applications. We propose on-CIS processing with an edge detection mask used in the readout circuit of the conventional CIS structure for high-speed lane detection. Furthermore, the edge detection mask can detect the edges of slanting lanes to improve accuracy. A prototype of the proposed CIS was fabricated using a 110 nm CIS process. It has an image resolution of 160 (H) × 120 (V) and a frame rate of 113, and it occupies an area of 5900 μm × 5240 μm. A comparison of its lane detection accuracy with that of existing edge detection algorithms shows that it achieves an acceptable accuracy. Moreover, the total power consumption of the proposed CIS is 9.7 mW at pixel, analog, and digital supply voltages of 3.3, 3.3, and 1.5 V, respectively.

scholarly journals Influence of Pixel Etching on Electrical and Electro-Optical Performances of a Ga-Free InAs/InAsSb T2SL Barrier Photodetector for Mid-Wave Infrared Imaging

Photonics ◽  
2021 ◽  
Vol 8 (6) ◽  
pp. 194
Author(s):  
Maxime Bouschet ◽  
Ulises Zavala-Moran ◽  
Vignesh Arounassalame ◽  
Rodolphe Alchaar ◽  
Clara Bataillon ◽  
...  
Keyword(s):  
Dark Current ◽  
Infrared Imaging ◽  
Diffusion Length ◽  
Lateral Diffusion ◽  
Pixel Detector ◽  
Dark Current Density ◽  
Etching Depth ◽  
Photo Response ◽  
Wet Chemical ◽  
Absorbing Layer

In this paper, the influence of etching depth on the dark current and photo-response of a mid-wave infrared Ga-free T2SL XBn pixel detector is investigated. Two wet chemical etching depths have been considered for the fabrication of a non-passivated individual pixel detector having a cut-off wavelength of 5 µm at 150 K. This study shows the strong influence of the lateral diffusion length of a shallow-etched pixel on the electro-optical properties of the device. The lowest dark current density was recorded for the deep-etched detector, on the order of 1 × 10−5 A/cm2 at 150 K and a bias operation equal to −400 mV. The corresponding quantum efficiency was measured at 60% (without anti-reflection coating) for a 3 µm thick absorbing layer. A comparison of experimental results obtained on the two kinds of etched pixels demonstrates the need for a deep-etching process combined with efficient passivation for FPA manufacturing.

scholarly journals Specific Absolute Velocity Thresholds during Male Basketball Games Using Local Positional System; Differences between Age Categories

2021 ◽  
Vol 11 (10) ◽  
pp. 4390
Author(s):  
Carlos Sosa ◽  
Alberto Lorenzo ◽  
Juan Trapero ◽  
Carlos Ribas ◽  
Enrique Alonso ◽  
...  
Keyword(s):  
Standard Deviation ◽  
Real Time ◽  
Effect Size ◽  
High Speed ◽  
Maximum Speed ◽  
Large Effect Size ◽  
Moderate Effect Size ◽  
Positional System ◽  
Moderate Effect ◽  
Distance Zone

The aim of this study was (I) to establish absolute specific velocity thresholds during basketball games using local positional system (LPS) and (II) to compare the speed profiles between various levels of competitions. The variables recorded were total distance (TD); meters per minute (m·min); real time (min); maximum speed (Km h−1), distance (m), percentage distance, and percentage duration invested in four speed zones (standing–walking; jogging; running; and high-speed running). Mean and standard deviation (±SD) were calculated, and a separate one-way analysis of variance was undertaken to identify differences between competitions. TD (3188.84 ± 808.37 m) is covered by standing–walking (43.51%), jogging (36.58%), running (14.68%), and sprinting (5.23%) activities. Overall, 75.22% of the time is invested standing–walking, jogging (18.43%), running (4.77%), and sprinting (1.89%). M·min (large effect size), % duration zone 2 (moderate effect size); distance zone 4 (large effect size), and % distance zone 4 (very large effect size) are significantly higher during junior than senior. However, % distance zone 1 (large effect size) and % duration zone 1 (large effect size) were largely higher during senior competition. The findings of this study reveal that most of the distance and play time is spent during walking and standing activities. In addition, the proportion of time spent at elevated intensities is higher during junior than in senior competition.

High-speed CMOS image sensor circuits with in situ frame storage

2004 ◽  
Vol 51 (4) ◽  
pp. 1648-1656 ◽  
Author(s):  
S. Kleinfelder ◽  
Yandong Chen ◽  
K. Kwiatkowski ◽  
A. Shah
Keyword(s):  
High Speed ◽  
Cmos Image Sensor ◽  
Image Sensor
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