Noise Reduction Effect of Multiple-Sampling-Based Signal-Readout Circuits for Ultra-Low Noise CMOS Image Sensors.

Sensors (Basel)

Research Institute of Electronics, Shizuoka University, Shizuoka 432-8011, Japan.

Published: November 2016

This paper discusses the noise reduction effect of multiple-sampling-based signal readout circuits for implementing ultra-low-noise image sensors. The correlated multiple sampling (CMS) technique has recently become an important technology for high-gain column readout circuits in low-noise CMOS image sensors (CISs). This paper reveals how the column CMS circuits, together with a pixel having a high-conversion-gain charge detector and low-noise transistor, realizes deep sub-electron read noise levels based on the analysis of noise components in the signal readout chain from a pixel to the column analog-to-digital converter (ADC). The noise measurement results of experimental CISs are compared with the noise analysis and the effect of noise reduction to the sampling number is discussed at the deep sub-electron level. Images taken with three CMS gains of two, 16, and 128 show distinct advantage of image contrast for the gain of 128 (noise(median): 0.29 e) when compared with the CMS gain of two (2.4 e), or 16 (1.1 e).

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5134526PMC
http://dx.doi.org/10.3390/s16111867DOI Listing

Publication Analysis

Top Keywords

noise reduction
12
image sensors
12
noise
8
reduction multiple-sampling-based
8
cmos image
8
signal readout
8
readout circuits
8
deep sub-electron
8
analysis noise
8
multiple-sampling-based signal-readout
4

Similar Publications

Work-related temporary hearing loss and associated factors among textile industry workers in Amhara region, Ethiopia: a cross-sectional study.

BMJ Open

December 2024

Department of Environmental and Occupational Health and Safety, College of Medicine and Health Science, Institute of Public Health, University of Gondar, Gondar, Ethiopia.

Objectives: This study was designed to assess occupational noise exposure levels, prevalence of temporary hearing loss and associated factors among textile industry workers in Amhara region, Ethiopia.

Design: An institution-based, cross-sectional study was conducted between June and July 2022. Participants were selected via a simple random sampling technique.

View Article and Find Full Text PDF

While gas chromatography mass spectrometry (GC-MS) has long been used to identify compounds in complex mixtures, this process is often subjective and time-consuming and leaves a large fraction of seemingly good-quality spectra unidentified. In this work, we describe a set of new mass spectral library-based methods to assist compound identification in complex mixtures. These methods employ mass spectral uniqueness and compound ubiquity of library entries alongside noise reduction and automated comparison of retention indices to library compounds.

View Article and Find Full Text PDF

Optimizing hip MRI: enhancing image quality and elevating inter-observer consistency using deep learning-powered reconstruction.

BMC Med Imaging

January 2025

Department of Magnetic Resonance Imaging, The First Affiliated Hospital, Zhengzhou University, Zhengzhou, 450052, China.

Background: Conventional hip joint MRI scans necessitate lengthy scan durations, posing challenges for patient comfort and clinical efficiency. Previously, accelerated imaging techniques were constrained by a trade-off between noise and resolution. Leveraging deep learning-based reconstruction (DLR) holds the potential to mitigate scan time without compromising image quality.

View Article and Find Full Text PDF

Audiovisual Breathing Guidance for Improved Image Quality and Scan Efficiency of T2- and Diffusion-Weighted Liver MRI.

Invest Radiol

January 2025

From the Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Bonn, Germany (N.M., A.I., A.L., L.B., T.D., D. Kravchenko, D. Kuetting, C.C.P., J.A.L.); Quantitative Imaging Lab Bonn (QILaB), Bonn, Germany (N.M., A.I., L.B., D. Kravchenko, D. Kuetting, J.A.L.); Philips Healthcare, Hamburg, Germany (C.K.); Philips Medical Systems, Eindhoven, the Netherlands (A.H.-M.); and Department of Diagnostic and Interventional Radiology, University Hospital Aachen, Aachen, Germany (C.Y.).

Objectives: Impaired image quality and long scan times frequently occur in respiratory-triggered sequences in liver magnetic resonance imaging (MRI). We evaluated the impact of an in-bore active breathing guidance (BG) application on image quality and scan time of respiratory-triggered T2-weighted (T2) and diffusion-weighted imaging (DWI) by comparing sequences with standard triggering (T2S and DWIS) and with BG (T2BG and DWIBG).

Materials And Methods: In this prospective study, random patients with clinical indications for liver MRI underwent 3 T MRI with standard and BG acquisitions.

View Article and Find Full Text PDF

The fractional nonlinear Schrödinger equation: Soliton turbulence, modulation instability, and extreme rogue waves.

Chaos

January 2025

KLMM, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China.

In this paper, we undertake a systematic exploration of soliton turbulent phenomena and the emergence of extreme rogue waves within the framework of the one-dimensional fractional nonlinear Schrödinger (FNLS) equation, which appears in many fields, such as nonlinear optics, Bose-Einstein condensates, plasma physics, etc. By initiating simulations with a plane wave modulated by small noise, we scrutinized the universal regimes of non-stationary turbulence through various statistical indices. Our analysis elucidates a marked increase in the probability of rogue wave occurrences as the system evolves within a certain range of Lévy index α, which can be ascribed to the broadened modulation instability bandwidth.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!