Sharpen Image

Enhance the details and edges in an image by applying a sharpening filter.

Request Parameters

Response

Returns the sharpened image in the same format as the input file.

Example Request

    // example.sh
curl -X POST "https://oyyi.xyz/api/image/sharpen"   -H "accept: application/json" \
  -H "Content-Type: multipart/form-data" \
  -F "file=@image.jpg" \
  --output sharpened.jpg
  

Example with Python

    // sharpen.py
import requests

url = "https://oyyi.xyz/api/image/sharpen"

files = {
    'file': open('image.jpg', 'rb')
}

data = {}

response = requests.post(url, files=files, data=data)

# Save the sharpened image
with open('sharpened.jpg', 'wb') as f:
    f.write(response.content)
  

Example with JavaScript

    // sharpen.js
// Using fetch API
const formData = new FormData();
formData.append('file', fileInput.files[0]);

fetch('https://oyyi.xyz/api/image/sharpen', {
  method: 'POST',
  body: formData
})
.then(response => response.blob())
.then(blob => {
  // Create a URL for the blob
  const url = URL.createObjectURL(blob);

  // Create a link to download the image
  const a = document.createElement('a');
  a.href = url;
  a.download = 'sharpened.jpg';
  a.click();

  // Clean up by revoking the URL
  URL.revokeObjectURL(url);
})
.catch(error => console.error('Error:', error));
  

Sharpening Methods

Sharpening Strength Examples

How It Works

Image sharpening works by increasing the contrast between adjacent pixels, particularly at edges:

• Unsharp Mask: Despite its name, this technique actually sharpens the image. It works by:
  1. Creating a blurred (unsharp) version of the original image
  2. Subtracting this blurred version from the original to identify edges
  3. Adding a weighted version of these edges back to the original image
• Laplacian: This method uses a Laplacian filter to detect areas of rapid intensity change (edges) and enhances them. It's more direct but can be more prone to enhancing noise.

Error Responses

Notes

• The sharpening effect is implemented using an unsharp mask filter by default, which enhances edges while minimizing noise amplification.
• Higher strength values will result in more pronounced sharpening but may introduce artifacts or noise.
• Sharpening is most effective on slightly blurry or soft images.
• Over-sharpening can create halos around edges and amplify noise, so use higher strength values with caution.
• The radius parameter (for unsharp mask) controls how wide the edge enhancement effect extends. Larger values affect wider areas around edges.
• The maximum file size allowed is 10MB.
• This operation preserves the alpha channel (transparency) if present in the original image.

Use Cases

• Enhancing details in slightly blurry photos
• Improving text readability in scanned documents
• Bringing out texture details in product photography
• Correcting soft focus in portraits
• Enhancing architectural or landscape photography
• Improving the clarity of images that will be printed