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Archives for May 12, 2025

How Sensor Noise Scales with Exposure Time

May 12, 2025 JimK Leave a Comment

When you increase the exposure time in a digital camera, you expect to collect more signal. But what happens to the noise? The answer depends on the source of the noise. Understanding how each one scales with exposure time helps you optimize your imaging strategy, especially in low-light or long-exposure situations. Let’s look at the… [Read More]

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Dark Current in CMOS Sensors: Where It Comes From, and How Cooling Helps

May 12, 2025 JimK Leave a Comment

In low-light or long-exposure photography, one of the most persistent sources of unwanted signal is dark current: thermally generated electrons that accumulate even in total darkness. Unlike read noise, which is largely constant from frame to frame, dark current grows with exposure time and varies from pixel to pixel. Dark current is the rate at… [Read More]

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What cooling can, and can’t, do for CMOS read noise

May 12, 2025 JimK Leave a Comment

Cooling a CMOS sensor reduces noise. But which noise? By how much? And is it worth the effort for your application? Let’s break it down by examining what cooling affects — and what it doesn’t — in the readout chain. First: What Do We Mean by “Read Noise”? Read noise includes all non-random and random… [Read More]

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Read Noise in CMOS Sensors: dual conversion gain

May 12, 2025 JimK Leave a Comment

Read noise sets the lower limit of a sensor’s usable dynamic range. It encompasses all noise sources between the pinned photodiode (PPD) and the final digital output. For modern CMOS sensors, this path is often split into two readout modes via dual conversion gain (DCG). Read noise includes: Reset noise at the floating diffusion (kTC… [Read More]

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Photon Transfer Curves: a unifying tool for analyzing sensor noise

May 12, 2025 JimK Leave a Comment

The Photon Transfer Curve (PTC), popularized by James Janesick in Photon Transfer, is a powerful tool for characterizing image sensors. It relates mean signal level to signal variance, capturing the behavior of multiple noise sources across the full dynamic range. The Basic Idea Plot the variance of the pixel output against the mean signal level… [Read More]

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Articles

  • About
    • Patents and papers about color
    • Who am I?
  • How to…
    • Backing up photographic images
    • How to change email providers
    • How to shoot slanted edge images for me
  • Lens screening testing
    • Equipment and Software
    • Examples
      • Bad and OK 200-600 at 600
      • Excellent 180-400 zoom
      • Fair 14-30mm zoom
      • Good 100-200 mm MF zoom
      • Good 100-400 zoom
      • Good 100mm lens on P1 P45+
      • Good 120mm MF lens
      • Good 18mm FF lens
      • Good 24-105 mm FF lens
      • Good 24-70 FF zoom
      • Good 35 mm FF lens
      • Good 35-70 MF lens
      • Good 60 mm lens on IQ3-100
      • Good 63 mm MF lens
      • Good 65 mm FF lens
      • Good 85 mm FF lens
      • Good and bad 25mm FF lenses
      • Good zoom at 24 mm
      • Marginal 18mm lens
      • Marginal 35mm FF lens
      • Mildly problematic 55 mm FF lens
      • OK 16-35mm zoom
      • OK 60mm lens on P1 P45+
      • OK Sony 600mm f/4
      • Pretty good 16-35 FF zoom
      • Pretty good 90mm FF lens
      • Problematic 400 mm FF lens
      • Tilted 20 mm f/1.8 FF lens
      • Tilted 30 mm MF lens
      • Tilted 50 mm FF lens
      • Two 15mm FF lenses
    • Found a problem – now what?
    • Goals for this test
    • Minimum target distances
      • MFT
      • APS-C
      • Full frame
      • Small medium format
    • Printable Siemens Star targets
    • Target size on sensor
      • MFT
      • APS-C
      • Full frame
      • Small medium format
    • Test instructions — postproduction
    • Test instructions — reading the images
    • Test instructions – capture
    • Theory of the test
    • What’s wrong with conventional lens screening?
  • Previsualization heresy
  • Privacy Policy
  • Recommended photographic web sites
  • Using in-camera histograms for ETTR
    • Acknowledgments
    • Why ETTR?
    • Normal in-camera histograms
    • Image processing for in-camera histograms
    • Making the in-camera histogram closely represent the raw histogram
    • Shortcuts to UniWB
    • Preparing for monitor-based UniWB
    • A one-step UniWB procedure
    • The math behind the one-step method
    • Iteration using Newton’s Method

Category List

Recent Comments

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  • Ivo de Man on Fuji 20-35/4 landscape field curvature at 23mm vs 23/4 GF

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