Measuring Intra-Pixel Sensitivity Variations of a CMOS Image Sensor

Mahato, Swaraj Bandhu; Meynants, Guy; Raskin, Gert; Winckel, H. Van

doi:10.1109/jsen.2018.2798698

Cited by 11 publications

(4 citation statements)

References 13 publications

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“…Street et al 2003;Christian et al 2006;Gillon et al 2008;Alonso et al 2008;Zhao et al 2014). High-end CCDs have almost exclusively been used for this work to mitigate contributions from intra-pixel (Mahato et al 2018) and inter-pixel sensitivity variations (e.g. Southworth et al 2009a,b;Mann et al 2011;Croll et al 2011;Fukui et al 2016) which impact photometric precision.…”

Section: Exoplanetsmentioning

confidence: 99%

The Huntsman Telescope

Spitler,

Longbottom,

Alvarado-Montes

et al. 2019

Preprint

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The Huntsman Telescope, located at Siding Spring Observatory in Australia, is a system of ten telephoto Canon lenses designed for low surface brightness imaging in the Southern sky. Based upon the Dragonfly Telephoto Array, the refractive lens-based system provides an obstruction free optical path, which reduces the number of scattering surfaces and allows easier access to lower surface brightness levels.In this proceeding, we present an analysis of the impact of flat fielding uncertainty on the limiting low surface brightness levels. We show that a fairly standard set of flat-field data can be well-characterised to a ∼ 0.1% level. This corresponds to a 5-σ lower limit of ∼ 33 magnitude per arcsecond 2 , which means that flat fielding is not likely going to set Huntsman's low surface brightness limit.We also present early results of an exoplanet transient mode for Huntsman where all lenses work together to detect subtle variations in the luminosity of relatively bright V = 8 − 12 magnitude stars. High-precision exoplanet imaging is ultimately limited by systematic uncertainties, so we anticipate multiple lenses will help to mitigate issues related to pixel-to-pixel and intra-pixel sensitivity variations. Our initial results show we can easily get ∼ 0.4% photometric precision with a single, defocused lens.

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Section: Exoplanetsmentioning

confidence: 99%

The Huntsman Telescope

Spitler,

Longbottom,

Alvarado-Montes

et al. 2019

Preprint

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“…Each pixel in a CMOS camera contains its own amplifier and A/D conversion circuit (Howell 2006). Consequently, the dark current and quantum efficiency exhibit nonuniformity between pixels, introducing additional noise that can adversely affect the detection efficiency, photometry, and astrometry accuracy (Mahato et al 2018).…”

Section: Introductionmentioning

confidence: 99%

A Data-driven Approach for Mitigating Dark Current Noise and Bad Pixels in Complementary Metal Oxide Semiconductor Cameras for Space-based Telescopes

Jia,

Lv,

et al. 2024

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In recent years, there has been a gradual increase in the performance of complementary metal oxide semiconductor (CMOS) cameras. These cameras have gained popularity as a viable alternative to charge-coupled device cameras in a wide range of applications. One particular application is the CMOS camera installed in small space telescopes. However, the limited power and spatial resources available on satellites present challenges in maintaining ideal observation conditions, including temperature and radiation environment. Consequently, images captured by CMOS cameras are susceptible to issues such as dark current noise and defective pixels. In this paper, we introduce a data-driven framework for mitigating dark current noise and bad pixels for CMOS cameras. Our approach involves two key steps: pixel clustering and function fitting. During the pixel clustering step, we identify and group pixels exhibiting similar dark current noise properties. Subsequently, in the function fitting step, we formulate functions that capture the relationship between dark current and temperature, as dictated by the Arrhenius law. Our framework leverages ground-based test data to establish distinct temperature–dark current relations for pixels within different clusters. The cluster results could then be utilized to estimate the dark current noise level and detect bad pixels from real observational data. To assess the effectiveness of our approach, we have conducted tests using real observation data obtained from the Yangwang-1 satellite, equipped with a near-ultraviolet telescope and an optical telescope. The results show a considerable improvement in the detection efficiency of space-based telescopes.

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“…Therefore, the Wiener or Lucy-Richardson deconvolution technique are often used to calculate IPS [13][14][15][16]. A disadvantage of deconvolution is that the low-amplitude high-frequency components are suppressed and information on small sensitivity variations in the pixel is lost [17]. Then, the model fitting method can also be used to calculate IPS based on the DSPR model.…”

Section: Introductionmentioning

confidence: 99%

“…Then, the model fitting method can also be used to calculate IPS based on the DSPR model. These include using a Bayesian posterior probability density function to fit the IPS parameter of Euclid Visible Instrument CCD [18] and a forward modeling technique to calculate the IPS of CMOS image sensors [17].…”

Section: Introductionmentioning

confidence: 99%

Improved Intra-Pixel Sensitivity Characterization Based on Diffusion and Coupling Model for Infrared Focal Plane Array Photodetector

Zhong

Zhu

et al. 2021

Sensors

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The high-precision characterization of the intra-pixel sensitivity (IPS) for infrared focal plane array (FPA) photodetector is of great significance to high-precision photometry and astrometry in astronomy, as well as target tracking in under-sampled remote sensing images. The discrete sub-pixel response (DSPR) model and fill factor model have been used for IPS characterization in some studies. However, these models are incomplete and lack the description of physical process of charge diffusion and capacitance coupling, leading to the inaccuracy of IPS characterization. In this paper, we propose an improved IPS characterization method based on the diffusion and coupling physical (DCP) model for infrared FPA photodetector, which considering the processes of generation and collection of the charge, can improve the accuracy of IPS characterization. The IPS model can be obtained by convolving the ideal rectangular response function with the charge diffusion function and the capacitive coupling function. Then, the IPS model is convolved with the beam spot profile to obtain the beam spot scanning response model. Finally, we calculate the parameters of IPS by fitting the beam spot scanning response map with the proposed DCP model based on the Trust-Region-Reflective algorithm. Simulated results show that when using a 3 μm beam spot to scan, the error of IPS characterization based on DCP model is 0.63%, which is better than that of DSPR model’s 3.70%. Experimental results show that the fitting error of the beam spot scan response model based on DCP model is 4.29%, which is better than that of DSPR model’s 8.31%.

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Measuring Intra-Pixel Sensitivity Variations of a CMOS Image Sensor

Cited by 11 publications

References 13 publications

The Huntsman Telescope

The Huntsman Telescope

A Data-driven Approach for Mitigating Dark Current Noise and Bad Pixels in Complementary Metal Oxide Semiconductor Cameras for Space-based Telescopes

Improved Intra-Pixel Sensitivity Characterization Based on Diffusion and Coupling Model for Infrared Focal Plane Array Photodetector

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