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Image Noise Reduction

Reduce image noise using multiple algorithms including median, gaussian, and bilateral filtering

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Quick start

Call this tool from your code in three languages.

cURL
# 1) Request a presigned URL → returns { uploadUrl, storageKey }
curl -X POST 'https://api.elysiatools.com/api/upload/presign/image-noise-reduction' \
  -H 'Content-Type: application/json' \
  -d '{"filename":"imageFile.ext","contentType":"application/octet-stream","size":12345}'

# 2) PUT the file bytes directly to the presigned uploadUrl
curl -X PUT '<presigned uploadUrl>' \
  --data-binary @/path/to/file.ext

# 3) Call the tool, passing the returned storageKey for each file field
curl -X POST 'https://api.elysiatools.com/en/api/tools/image-noise-reduction' \
  -F 'imageFile=uploads/2026/01/01/your-tool-1700000000000-abc123.ext' \
  -F 'algorithm=median' \
  -F 'strength=1' \
  -F 'kernelSize=3' \
  -F 'iterations=1' \
  -F 'preserveEdges=true' \
  -F 'format=original' \
  -F 'quality=95'

© 2026 Elysia Tools. Developer documentation.

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API reference

Send a POST request with your inputs as JSON. File parameters require a separate upload first.

Endpoint

HTTP
POST https://api.elysiatools.com/en/api/tools/image-noise-reduction

Parameters

NameTypeRequiredDescription
imageFilefileupload requiredYesUpload any image file (JPEG, PNG, WebP, GIF, BMP, TIFF) to reduce noise and improve image quality
algorithmselectNoChoose the denoising algorithm. Median works well for salt & pepper noise, Gaussian for random noise
strengthrangeNoStrength of noise reduction. Higher values remove more noise but may blur details
kernelSizerangeNoSize of the filter kernel (must be odd). Larger kernels remove more noise but may blur details
iterationsnumberNoNumber of denoising passes. More iterations = stronger noise reduction
preserveEdgescheckboxNoMaintain edge detail while removing noise. Recommended for photos with important details
formatselectNoChoose output format or keep original. PNG recommended for maximum quality
qualitynumberNoOutput quality for lossy formats (JPEG, WebP). Higher = better quality but larger file size
File-type parameters must be uploaded first via POST /upload/image-noise-reduction, then the returned filePath is passed to the corresponding file field.

Response format

File result

JSON
{
  "filePath": "/public/processing/randomid.ext",
  "fileName": "output.ext",
  "contentType": "application/octet-stream",
  "size": 1024,
  "metadata": {
    "key": "value"
  },
  "error": "Error message (optional)",
  "message": "Notification message (optional)"
}

MCP integration

Add this tool to your Model Context Protocol server so AI agents can list and call it.

Server configuration

Add this block to your MCP client configuration:

mcp.json
{
  "mcpServers": {
    "elysiatools-image-noise-reduction": {
      "name": "image-noise-reduction",
      "description": "Reduce image noise using multiple algorithms including median, gaussian, and bilateral filtering",
      "baseUrl": "https://api.elysiatools.com/mcp/sse?toolId=image-noise-reduction",
      "command": "",
      "args": [],
      "env": {},
      "isActive": true,
      "type": "sse"
    }
  }
}

List available tools

After connecting to the SSE endpoint, list the exposed tools:

tools/list
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/list"
}

Call this tool

Invoke the tool by its id, passing arguments built from its parameters:

tools/call
{
  "jsonrpc": "2.0",
  "id": 2,
  "method": "tools/call",
  "params": {
    "name": "image-noise-reduction",
    "arguments": {
  "imageFile": "https://example.com/file.ext",
  "algorithm": "median",
  "strength": 1,
  "kernelSize": 3,
  "iterations": 1,
  "preserveEdges": true,
  "format": "original",
  "quality": 95
}
  }
}
Chain multiple tools in one session with a comma-separated toolId list, e.g. /mcp/sse?toolId=png-to-webp,jpg-to-webp,gif-to-webp (max 20).
File parameters accept a public file URL only (https://…). Local paths, data: URIs, and Base64 strings are not supported.

Questions or issues? Contact [email protected]

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