Moiré (also written moire) is a false interference pattern of waves, bands or colored fringes that appears when a fine repeating structure in the scene interacts with the regular pixel grid of a camera sensor or a display. In photography it is an image quality defect caused by aliasing: the sensor samples detail that is finer than it can resolve, and the excess detail reappears as a coarser pattern that does not exist in the subject.
Moiré typically shows up on fabrics, screens, brick walls, window blinds, feathers and architectural grids. It is closely linked to sharpness and resolution, because the conditions that produce the most detailed images, such as sharp lenses and sensors without optical low-pass filters, also make moiré more likely.
How moiré forms on a camera sensor
Moiré forms when two regular patterns overlap at slightly different spacing or angle. In a camera, one pattern is the subject, for example the weave of a shirt, and the other is the pixel grid with its fixed pitch. When the subject detail approaches or exceeds the Nyquist limit, which is half the sampling frequency of the sensor, it cannot be recorded correctly.
Instead, the high-frequency detail is folded back as a low-frequency pattern, an effect known as aliasing. The resulting bands can be much larger than the original structure, and they change shape with small shifts in distance, focus or angle, which is why moiré can appear in one frame and vanish in the next.
Most sensors add a further complication: a Bayer color filter array samples red and blue at lower density than green. Fine detail therefore aliases differently in each color channel, and demosaicing turns the mismatch into color moiré, the rainbow-like fringes typical of photographed textiles.
Types of moiré in photography
Photographers usually distinguish moiré by its appearance and by where in the imaging chain it arises. The distinction matters because each type needs a different remedy.
| Type | Appearance | Main cause | Typical subjects |
|---|---|---|---|
| Luminance moiré | Gray waves or bands | Aliasing of fine detail in brightness | Architecture grids, blinds, fences |
| Color moiré | Rainbow fringes and blotches | Different sampling of color channels | Fabrics, suits, feathers, hair |
| Screen moiré | Strong waves over displayed images | Display pixel grid against sensor grid | Photographing monitors and phones |
| Scan and print moiré | Regular rosettes or banding | Halftone dots against scanner or printer grid | Scanned magazines and reproductions |
| Display moiré | Pattern visible only at some zoom levels | Resampling for screen preview | Image viewed at reduced size |
Display moiré is a frequent false alarm. A pattern that appears at 33 or 50 percent view but disappears at 100 percent magnification comes from the preview scaling, not from the file itself.
Factors that increase or reduce moiré
The risk of moiré depends on the relationship between subject detail, lens resolution and pixel pitch. Any factor that delivers very fine, high-contrast detail exactly at the sensor’s sampling limit raises the risk.
| Factor | Higher moiré risk | Lower moiré risk |
|---|---|---|
| Optical low-pass filter | Absent or weak | Present and matched to pixel pitch |
| Pixel pitch | Detail near the sampling limit | Much higher pixel density than subject detail |
| Lens sharpness | Very sharp lens at optimal aperture | Softer lens or small aperture with diffraction |
| Focus | Pattern in the exact focal plane | Pattern slightly out of focus |
| Subject distance | Pattern period matches pixel spacing | Closer or farther so period changes |
| Color filter design | Standard Bayer array | Arrays with different layouts or monochrome sensors |
An optical low-pass filter (OLPF), also called an anti-aliasing filter, slightly blurs the image before sampling so that detail beyond the Nyquist limit does not reach the sensor. Many high-resolution cameras omit it to gain acutance and fine detail, accepting a higher risk of moiré.
Moiré compared with related image artifacts
Moiré is often confused with other defects that also produce patterns or colors. Telling them apart prevents photographers from applying the wrong correction.
| Artifact | Origin | Distinguishing feature |
|---|---|---|
| Moiré | Aliasing of repeating detail | Large waves that change with small shifts |
| Purple fringing | Chromatic aberration or sensor blooming | Colored edges along high-contrast borders |
| Chromatic noise | Random sensor noise in color channels | Irregular color speckles, worse at high ISO |
| Demosaicing artifacts | Interpolation errors at fine edges | Zipper or maze patterns on single edges |
| Banding | Read noise or quantization | Straight horizontal or vertical stripes |
Preventing and removing moiré
The most reliable strategy is to change the capture geometry, because moiré in a recorded file can be reduced but never perfectly reconstructed. Small changes are often enough to move the pattern away from the sensor’s sampling frequency.
- Change distance or focal length slightly so the period of the pattern no longer coincides with the pixel spacing.
- Rotate the camera a few degrees, since the interference depends on the angle between the two grids.
- Shift focus slightly off the patterned area or use a smaller aperture, accepting a small loss of sharpness.
- Check at 100 percent on the camera or a tethered screen during critical work such as fashion and product shoots.
- Use a moiré removal brush in raw processing to suppress color moiré locally; luminance moiré is much harder to remove convincingly.
- When photographing screens, match the shutter speed to the refresh rate and move until the waves disappear, or defocus very slightly.
Some cameras offer pixel shift multi-shot modes that capture full color at every pixel position, which largely removes color moiré on static subjects. They do not work with moving subjects or handheld shooting in most implementations.
A plain-language summary
If you have ever photographed a striped shirt or a computer screen and seen strange waves or rainbow ripples that were not really there, you have seen moiré.
It happens because the camera sensor is a grid of tiny squares. When the subject also has a very fine grid or pattern, the two patterns clash, much like two window screens laid on top of each other. A small move closer, farther or at a slight angle usually makes the effect disappear.
An example from practice
A product photographer shoots a catalog of men’s suits with a 45 megapixel camera that has no optical low-pass filter. On a fine herringbone jacket, the tethered screen at 100 percent shows colored ripples across the shoulders, although the fabric itself is plain gray.
She moves the camera back about 20 centimeters, refocuses and recrops slightly, and stops down from f/8 to f/11. The pattern weakens but some color remains in one fold, so she applies a local moiré reduction brush during raw processing. The final catalog image shows clean fabric texture without false color, and she adds the distance change to her standard setup for that garment type.