Remove digital noise and graininess from photos using a median filter — the most effective noise reduction technique that preserves edges and detail. Control strength with a slider, compare before/after, and process multiple images in bulk.
Drag and drop one or more noisy or grainy images. The median filter works best on photos taken in low-light conditions, high-ISO camera shots, scanned documents with paper grain, or images with JPEG compression artifacts.
Use the strength slider to control how aggressively the median filter is applied. Low strength (1–2) gently smooths noise while fully preserving fine detail. High strength (3–5) removes heavy grain but may slightly soften sharp edges — a trade-off typical of all noise reduction.
Toggle the Before/After comparison slider to see the noise reduction effect on your image. For best results, check sharp edges and fine text to ensure they remain acceptable before downloading. Bulk mode processes all images with the same strength setting.
A median filter works by examining each pixel and its surrounding neighbours, sorting all the values, and replacing the centre pixel with the median (middle) value. Unlike a blur filter (which averages all values and softens edges), the median filter naturally rejects isolated extreme values — which is exactly what noise is. Noise pixels have values very different from their neighbours, so they end up at the extremes of the sorted list and get replaced by a representative median value. Edges, which have consistently different values from one side to the other, are largely preserved.
The median filter is most effective for salt-and-pepper noise (random isolated bright and dark pixels), which is common in high-ISO photos and scanned images. It also reduces Gaussian noise (random variation throughout the image) and JPEG compression blockiness. It is less effective for fine luminance noise across large areas, which typically requires dedicated AI-powered denoising software.
At low strength settings (1–2), edge detail is largely preserved because the median filter is edge-aware. At higher settings (4–5), some fine texture and very sharp edges may be slightly softened — this is an inherent trade-off in all noise reduction. For the best balance of noise reduction and sharpness, start at strength 2 and increase only if noise is still visible after checking the Before/After comparison.
The median filter significantly reduces high-ISO noise and makes images much cleaner, but very heavy noise (ISO 6400+ on crop sensors) may require multiple passes or dedicated AI denoising software (like Topaz DeNoise or Lightroom Denoise) for optimal results. Use this tool for moderate noise reduction, portrait cleanup, scanned photo restoration, and removing compression artifacts.
Yes — bulk mode applies the same noise reduction strength to all uploaded images and packages them into a ZIP download. This is useful for cleaning up a batch of low-light photos, restoring a set of scanned old photographs, or removing consistent JPEG artifacts from a product image library.
Blurring (Gaussian or Box) averages all surrounding pixels equally, which softens everything including real edges and fine detail. Noise removal using a median filter specifically targets isolated aberrant pixels (noise) while leaving consistent transitions (edges) intact. For photos, always prefer median-based noise removal over blur — blur will make your image look soft and unfocused whereas noise removal reduces grain while keeping the subject crisp.
