MTF Analyzer
Analyze the modulation transfer function of an image sensor system, combining pixel aperture, optical diffraction, and defocus contributions to understand spatial resolution limits.
MTF Analyzer
Interactive Modulation Transfer Function analyzer. Explore how pixel aperture and diffraction optics limit spatial resolution.
MTF Curves
Bar Target Simulation
Model scope
Use this browser tool for intuition, relative trends, and design-space exploration. Its local simplified model is not a substitute for RCWA/FDTD sign-off, silicon calibration, or vendor process data.
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Modulation Transfer Function
MTF asks a simple question: how much contrast survives as image detail gets finer? Big bold patterns transfer almost perfectly, but as you zoom into stripe patterns close to the pixel size, contrast falls away. This analyser combines two limits — finite pixel size acting as a low-pass filter, and lens diffraction blur — to predict where the detail finally vanishes.
MTF describes how contrast is transferred as a function of spatial frequency. The analyzer combines pixel aperture and diffraction limits.
Assumptions
- The compact MTF model assumes linear, shift-invariant transfer and separable aperture/diffraction effects.
- Lens aberration, demosaic, sharpening, motion blur, and charge diffusion are not explicitly solved.
- Pixel aperture is treated as an ideal rectangular integration window controlled by pitch and fill factor.
Outputs
- Pixel aperture MTF, diffraction cutoff, Nyquist frequency, combined MTF proxy, and MTF50-style landmarks.
- A diagnosis of whether sampling, aperture blur, or diffraction is the first-order resolution limiter.
Validation Example
- Reducing pixel pitch should raise Nyquist frequency but can make diffraction and aperture effects more visible relative to pitch.
- Increasing f-number should lower diffraction cutoff and suppress high-frequency contrast.
Core Equations
- \(f\): Spatial frequency
- \(p\): Pixel pitch
- \(FF\): Fill factor
A rectangular aperture low-pass filters the sampled image.
- \(f_c\): Cutoff frequency
No ideal incoherent diffraction-limited contrast remains beyond the cutoff.
- \(f_N\): Nyquist sampling limit
Sampling above Nyquist aliases into lower spatial frequencies.
Model Interpretation
- Pixel pitch controls sampling; f-number and wavelength control diffraction blur.
- The combined MTF is a product only under simplified linear, shift-invariant assumptions.
- ISO 12233/SFR measurements are system-level tests, not just pixel physics.
Frequency Landmarks
- The Nyquist limit $f_N=1/(2p)$ tells where sampled detail begins to alias.
- The diffraction cutoff $f_c=1/(\lambda N)$ tells the optical passband limit for an ideal aperture.
- The practical resolution limit is whichever term suppresses contrast first: pixel aperture, diffraction, lens aberration, or processing.
Measurement Notes
- Slanted-edge SFR estimates system MTF from an image, including optics, sensor sampling, demosaic, and sharpening.
- MTF50 is a convenient scalar, but full-curve shape matters for aliasing and texture rendering.
- Compare luminance and chroma MTF separately for Bayer sensors because demosaic changes each channel differently.
Known Missing Physics
- The compact model assumes linear shift-invariant behavior; real image pipelines may be nonlinear and adaptive.
- It does not include motion blur, focus error, lens field curvature, or rolling-shutter effects.
- Pixel optical crosstalk and charge diffusion can reduce high-frequency contrast beyond aperture MTF.