concept

Median Filtering

Median filtering is a non-linear digital signal processing technique used to reduce noise, particularly salt-and-pepper noise, in images or other data by replacing each pixel's value with the median value of its neighboring pixels within a defined window. It preserves edges better than linear filters like Gaussian blur, making it effective for smoothing while maintaining sharp transitions. This method is widely applied in image processing, computer vision, and data analysis to enhance quality without blurring important features.

Also known as: Median Filter, Median Smoothing, Non-linear Filtering, Salt-and-Pepper Noise Reduction, Edge-Preserving Smoothing

🧊Why learn Median Filtering?

Developers should learn median filtering when working on image processing tasks such as noise reduction in photographs, medical imaging, or computer vision applications where preserving edges is crucial. It is particularly useful in real-time systems or embedded devices due to its computational simplicity and effectiveness against impulse noise. For example, it can be applied in autonomous vehicles to clean up sensor data or in mobile apps for photo enhancement.