Image Median Filter
Apply a median filter to reduce noise in images while preserving edges and details. This powerful noise reduction tool is especially effective at removing salt-and-pepper noise, speckles, and random artifacts from photos without blurring important edge details. Perfect for cleaning up scanned images, digital photos, or images with compression artifacts.
Frequently Asked Questions
A median filter is a noise reduction technique that replaces each pixel with the median value of neighboring pixels. Unlike blur filters that average pixels, the median filter preserves edges better while effectively removing random noise and speckles from your images.
Use a median filter when you need to remove salt-and-pepper noise, random speckles, or isolated pixel errors while maintaining sharp edges. It's ideal for scanned documents, photos with sensor noise, or images with compression artifacts where you want to preserve detail.
The median filter causes minimal blurring compared to traditional blur filters. It's specifically designed to preserve edges and sharp transitions while removing noise, making it excellent for images where maintaining detail is important.
The median filter excels at removing impulse noise, also known as salt-and-pepper noise, which appears as random white and black pixels. It's also effective against speckle noise and isolated pixel errors common in digital photography and scanned images.
The median filter strength is typically controlled by the filter radius or kernel size. A larger radius will remove more noise but may also reduce fine details. Start with a small radius and increase if needed for better noise reduction.
The median filter works with all major image formats including JPG, PNG, WebP, GIF, TIFF, and BMP. The output format matches your input format, preserving compatibility while applying the noise reduction effect to your images.
Median filtering selects the middle value from neighboring pixels, while Gaussian blur averages them with weighted importance. This makes median filtering superior for removing impulse noise while preserving edges, whereas Gaussian blur creates smoother results but loses edge definition.
Yes, median filtering is excellent for reducing JPEG compression artifacts, block noise, and other compression-related distortions. It smooths out these artifacts while maintaining important image details and edges, making compressed images look cleaner and more professional.
Absolutely. Professional photographers use median filtering to clean up sensor noise in high-ISO shots, remove dust spots from scanned negatives, and reduce digital noise while maintaining critical sharpness in portrait and landscape photography. It's a non-destructive way to improve image quality.
For subtle noise reduction in portraits or detailed photos, use a small filter size (3-5 pixels). Medium sizes (5-7 pixels) work well for general purpose noise removal. Larger sizes (7-11 pixels) are best for heavily noisy images or scanned documents, though they may soften fine details.