# Remove Image Noise with a Median Filter Clean salt-and-pepper dots, scanner dust and speckle out of a photo with a median filter that keeps edges sharp. Adjustable window, channels and passes, in your browser. ## Run it - **CLI:** `gizza tool image-median-denoise 'url=https://example.com/input' 'radius=1' 'target=both' 'channels=all' 'passes=1' 'format=keep' 'quality=92' 'strip_metadata=true'` - **Web:** https://gizza.ai/tools/image-median-denoise/ - **Agents:** machine-readable descriptor (parameters JSON Schema) at https://gizza.ai/tools/image-median-denoise/tool.json ## Inputs - `image` — Image _(file; accept: image/*)_ - `radius` — Window radius (px) — window is 2×radius+1 _(field)_ - `target` — Specks to remove _(field)_ - `channels` — Channels to filter _(field)_ - `passes` — Passes _(field)_ - `format` — Output format _(field)_ - `quality` — Quality (jpg/webp only) _(field)_ - `strip_metadata` — Strip metadata (EXIF, camera info) _(field)_ ## Output - Denoised image (image) ## Query parameters Open the tool pre-filled and auto-run via URL: - `radius` — Window radius (px) — window is 2×radius+1 - `target` — Specks to remove - `channels` — Channels to filter - `passes` — Passes - `format` — Output format - `quality` — Quality (jpg/webp only) - `strip_metadata` — Strip metadata (EXIF, camera info) - `url` — fetch the input file from a public URL (CORS-permitting) Example: `https://gizza.ai/tools/image-median-denoise/?url=https://example.com/input&radius=1&target=both&channels=all&passes=1&format=keep&quality=92&strip_metadata=true` --- ## What a median filter does A median filter slides a small square window over the image and replaces the centre pixel with the **middle value** of everything inside that window. Because the middle value is a real pixel from the neighbourhood — not an average — a lone white or black dot has no influence at all: it sorts to the end of the list and is thrown away, while the edge running through the window keeps its two populations of pixels and stays exactly where it was. That is why median filtering is the standard answer to **salt-and-pepper noise** (scattered black/white dots from bad sensor pixels, transmission errors or a dusty scan) and why it beats a Gaussian blur, which smears the dot into a grey smudge and softens every edge along with it. ### Worked example Take a 3-pixel-wide row of a photo where one pixel has been hit by noise: ``` neighbours: 118 120 255 121 119 sorted: 118 119 120 121 255 median: 120 ``` The blown-out `255` is discarded and the pixel becomes `120`, matching its neighbours. An average would have produced `146` — a visible bright smudge. On this page: upload a noisy image, leave **Window radius** at `1` (a 3×3 window) and press run. Single-pixel dots are gone and the result downloads in the same format you uploaded. Raise the radius to `2` (5×5) for scanner dust or speckle that covers a couple of pixels. ### The controls - **Window radius** — the window is `2 × radius + 1` square. `1` = 3×3, `2` = 5×5, `5` = 11×11, `20` = 41×41. Bigger windows erase bigger blobs of noise but also erase fine texture, and the filter gets quadratically slower. - **Specks to remove** — *both* is the true median. *Bright only* leans toward the darker neighbours, so white dust is wiped harder (the image darkens a little); *dark only* does the reverse for black specks on light paper. - **Channels to filter** — *all* cleans everything. *Luma only* smooths brightness noise while colour detail is untouched. *Chroma only* removes the blotchy red/green patches of high-ISO colour noise and leaves luminance detail pin-sharp — usually the best-looking option for photos. - **Passes** — running a small window twice removes dense noise more gently than one large window, because each pass only ever moves a pixel to a value that already exists nearby. - **Output format / quality** — *keep* returns the format you uploaded; PNG is lossless; JPG and WebP use the quality slider (1–100, default 92). - **Strip metadata** — drops EXIF, camera info and comments from the output. ### Limits and edge cases - Input files up to **8 MB**, any format your browser's decoder handles (PNG, JPG, WebP, GIF, BMP, TIFF). - Radius is capped at **20** (a 41×41 window) and passes at **3**. Large radius values on a multi-megapixel photo can take a while — the work grows with the square of the window. - The median filter removes *impulse* noise. Fine film grain or heavy Gaussian sensor noise is better handled by a dedicated grain/denoise pass; a median filter will just flatten texture. - Text, thin lines and small dots are also "isolated pixels": at radius 3 and above, fine line art and small type start to erode. Keep the window as small as it can be while still catching the noise. - *Luma only* and *chroma only* convert the image through Y'CbCr, which can shift untouched channels by ±1 sRGB step. *All* filters the image in its native planar layout, with no colour conversion. - Choosing PNG, JPG or WebP for an animated GIF keeps only the first frame; *keep* filters every frame and stays animated. ## FAQ
What is the difference between a median filter and a blur? A blur averages the pixels in the window, so a bright noise dot contaminates every pixel around it and edges soften. A median *selects* a value that already exists in the window, so an outlier is discarded outright and a straight edge stays straight. For salt-and-pepper noise the median wins clearly; for smooth grain, a blur or a dedicated denoiser is a better fit.
What radius should I use? Start at `1` (a 3×3 window) — it removes single-pixel dots with almost no loss of detail. Use `2` (5×5) if the specks are 2–3 pixels wide, such as dust on a scan. Above `4` the image starts to look like a watercolour, so if you need that much cleaning, try 2 passes at a small radius instead of one big window.
Why does the result look flat or "painted"? Because the window is too large for the detail in the image. Every pass replaces texture with the local middle value, so fine grain, skin texture and small type get flattened. Lower the radius, drop to a single pass, or switch **Channels to filter** to *chroma only* so luminance detail is left completely untouched.
Can it clean up a scanned document? Yes — that is the classic use. A radius of 1–2 with *dark only* removes pepper specks from light paper without eating the strokes of the text, and *bright only* removes white pinholes from a dark background. Choose PNG output so the cleaned scan is not re-compressed, and tick **Strip metadata** if you are about to publish it.
Are my images uploaded anywhere? No. The filter runs in your browser through a WebAssembly build of ffmpeg. The file you pick is read locally, processed locally, and the download link points at the result held in your own tab's memory.
## Related tools - [Detect Edges in an Image](https://gizza.ai/tools/edge-detection/): Detect edges in a photo with the Canny or Sobel operator and download the edge map. Adjustable thresholds, noise blur and inverted line art, all in your browser. - [Compress an Image](https://gizza.ai/tools/image-compress/): Shrink an image's file size right in your browser — re-encode a JPG, PNG, or WebP at a chosen quality, same format out. No upload to a server, runs locally, free. - [Add a Drop Shadow to an Image](https://gizza.ai/tools/image-drop-shadow/): Add a realistic soft drop shadow behind a transparent PNG cutout — set offset, blur, color and opacity. Runs in your browser, nothing is uploaded, free. - [Add Film Grain to an Image](https://gizza.ai/tools/image-film-grain/): Add realistic analog film grain to a photo, right in your browser — adjustable amount, neutral or colored grain, optional format convert. Nothing is uploaded, free. - [Add a Vignette to an Image](https://gizza.ai/tools/image-vignette/): Add a dark, light or colored vignette around the edges of a photo, right in your browser — adjustable strength, center and output format. Nothing is uploaded, free.