Blur & Sharpen
Compare Gaussian blur, median filtering, bilateral smoothing, and unsharp masking for denoising and edge-aware sharpening.
Apply various blur and sharpen filters to images. Gaussian smoothing for noise reduction, median for salt-and-pepper noise, bilateral for edge-preserving smoothing, or unsharp mask for sharpening.
How to Use Blur & Sharpen
- Upload an image: Upload one of the formats listed by the tool (JPG, PNG, WebP) and wait for the local preview.
- Adjust settings and process: Choose the filter type (Gaussian Blur, Median, Bilateral, or Unsharp Mask) and adjust the strength parameters.
- Review and download: Review the result, then download it in one of the formats offered by this tool.
Frequently asked questions
What is Gaussian blur?
Gaussian blur smooths an image by averaging each pixel with its neighbors using a Gaussian (bell curve) weighted kernel. It reduces noise and detail while preserving overall structure.
What is bilateral filtering?
Bilateral filter smooths images while preserving edges. It considers both spatial distance and intensity difference, making it ideal for noise reduction without blurring object boundaries.
When should I use bilateral filter instead of Gaussian blur?
Use bilateral filtering when you need to smooth noise while keeping edges sharp. For example, skin smoothing in portraits or denoising photos. Gaussian blur treats all pixels equally and will blur edges. Bilateral filter considers both spatial distance and color similarity.
Is the Blur & Sharpen tool free?
Yes. All tools on Pixlane are free with no signup required.
Does it reuse cached assets on repeat visits?
Browser caching can speed repeat visits; uncached site assets can still require an internet connection.
What image formats are supported?
JPG, PNG, and WebP are supported.
What is an unsharp mask and how does it sharpen images?
Unsharp mask works by subtracting a blurred copy of the image from the original, then adding the difference back scaled by an amount. This enhances edges and fine details. The kernel size controls the blur radius and the strength determines how much sharpening is applied.
How does kernel size affect blur strength?
Larger kernel sizes (e.g., 15x15, 31x31) produce stronger blur by averaging more neighboring pixels. Kernel size must be odd. For subtle smoothing use 3-5; for heavy blur or bokeh-like effects use 15-31.