Unsharp masking

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Unsharp masking

Unsharp masking is an image sharpening technique that enhances the contrast of the edges in an image. Despite its name, the technique does not actually make the image unsharp. Instead, it increases the apparent sharpness by amplifying high-frequency components.

History

Unsharp masking originated in the field of photography and was initially a darkroom technique. The process involved creating a blurred, or "unsharp," negative of the original image and then combining it with the original negative. This technique was adapted for digital image processing and is now widely used in digital photography, graphic design, and image editing software.

Process

The unsharp masking process involves three main steps:

1. **Blurring the image**: A blurred version of the original image is created using a Gaussian blur or another blurring technique.
2. **Subtracting the blurred image**: The blurred image is subtracted from the original image to create a mask that highlights the edges.
3. **Combining the mask with the original image**: The mask is then added back to the original image, enhancing the edges and increasing the overall sharpness.

Parameters

Unsharp masking typically involves adjusting three parameters:

• **Amount**: Controls the strength of the sharpening effect.
• **Radius**: Determines the size of the edges to be enhanced.
• **Threshold**: Sets the minimum contrast level that will be sharpened, helping to avoid amplifying noise.

Applications

Unsharp masking is used in various fields, including:

• Digital photography: To enhance the sharpness of photos.
• Graphic design: To improve the clarity of images used in designs.
• Medical imaging: To enhance the details in medical images such as X-rays and MRI scans.

Related Techniques

• High-pass filter: Another technique used for image sharpening.
• Deconvolution: A method used to reverse the effects of blurring in images.
• Edge detection: A process used to identify the boundaries within an image.

See Also

• Image processing
• Image editing
• Digital photography
• Gaussian blur
• High-pass filter
• Edge detection