Find the sweet spot
See exactly where grain disappears and where fine detail starts to smear.
See how much grain you can remove before details turn to mush. Compare simple denoise filters on your own photo with a draggable before and after divider.
Left of the line: original. Right: denoised. Drag on the image to move the divider.
Runs entirely in your browser. Nothing is uploaded to any server.
See exactly where grain disappears and where fine detail starts to smear.
Median, bilateral and smoothing filters handle noise very differently.
Clean up grainy night and indoor photos before sharing.
A median filter replaces each pixel with the middle value of its 3 by 3 neighborhood. It removes isolated specks and salt-and-pepper noise very well while keeping hard edges, but repeated passes can flatten fine texture. A smoothing filter averages neighbors, which hides grain but also blurs edges.
The bilateral filter is an edge-preserving average: neighbors only count strongly when their brightness is close to the center pixel. Smooth areas get cleaned while edges, where brightness jumps, stay sharp. Edge sensitivity controls how big a jump counts as an edge, and the strength slider blends the result with the original.
Best general choice for photos with fine grain.
Best for dust, specks and salt-and-pepper noise.
A simple baseline that shows what plain blurring does.
Try bilateral first for camera grain. Use median when you see random bright or dark specks. Smoothing is mostly useful for comparison.
Too much noise reduction removes texture along with noise. Lower the passes or the strength, or reduce the edge sensitivity for the bilateral filter.
No. These are classic filters that run quickly in your browser. They are great for previews and moderate noise, while AI tools can recover more detail from very noisy images.
Photos are processed at up to 1200 pixels on the longest side to keep the preview fast.
No. All filtering happens on your device.
More free tools from My Panda Toolbox.