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Filter a picture

Blur effects for a photoBlur a photo, softly or with motion

A gentle all-over blur or a sideways smear. Pick how strong, then download.

The original photo, before any filterBeforeThe same photo with Soft blur applied by this pageSoft blur
Before and after: Soft blur, made by this page from one of our own photos.
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From photo to filtered in seconds

  1. Choose a photo

    Tap the button, drop a file or paste a screenshot. Any everyday photo works.

  2. Tap a look

    Every look is tried on your own picture. Drag across the photo to make it stronger or softer.

  3. Download

    Save it full size as JPG, PNG or WebP. No account, no watermark on your picture.

Choose a blur construction. Soft two-axis averaging or a deliberate horizontal or vertical smear, with the radius stated in pixels.

This is a rebuild: your photo is taken apart and remade, not just recoloured. It runs in this tab and nothing is uploaded.

Tip Hard edges, lights and text reveal direction clearly; an already soft photograph may show little change at small radii.

The operation behind the appearance

The soft style averages a horizontal neighbourhood and then averages the result vertically. Directional styles perform only one pass. Every output pixel is therefore an explicit mean of a rectangular line or area, with no semantic subject detection and no hidden depth estimate.

The controls are measurements

Blur direction
Two-axis soft, horizontal smear or vertical smear.
Radius
How far the average reaches on each active axis.

Where the construction breaks

A uniform radius treats foreground, subject and distant background equally. It cannot reproduce optical depth of field. Directional blur can also make bright points stretch into bands that dominate the frame, and a large two-axis radius can erase the exact subject separation the image needed.

The preview, draft and export all run the same kernel. Parameters measured in pixels are scaled with the source, so a chosen tile, band or radius does not become unexpectedly finer in the downloaded file.

Questions about this effect

Is soft blur Gaussian?

No. It is a separable box average: horizontal then vertical. The algorithm is stated because its edge response differs from a Gaussian even when both look soft.

What do horizontal and vertical modes simulate?

A one-axis average produces a directional smear. It can suggest motion, but it is not deconvolution and does not estimate what a camera actually did.

Why does a large radius darken or lighten edges?

Samples outside the frame are clamped to the nearest edge pixel. A strong border colour therefore contributes repeatedly near the boundary.

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