Image transformations
What is a binarization ?
What is a convolution ?
No, filtering operations such as mean filtering are not considered morphological operations. They are part of a different category of image processing techniques known as spatial filtering or convolutional filtering.
Filtering Operations
Purpose
Filtering operations like mean filtering (or averaging) are used to smooth images, reduce noise, and sometimes enhance specific features such as edges.
How It Works
Mean filtering involves convolving an image with a filter kernel (e.g., a 3x3 matrix where each value is 1/9). This operation computes the average of the pixel values within the kernel’s neighborhood and assigns this average to the central pixel.
Common Types of Filters
Mean Filter: Reduces noise by averaging the pixel values in the neighborhood.
Gaussian Filter: Applies a Gaussian function for weighted averaging, often used for blurring.
Median Filter: Replaces the central pixel with the median of the neighborhood values, effective at reducing salt-and-pepper noise.
Morphological Operations
Purpose
Morphological operations are used to process the shape or structure of objects within an image, such as removing noise, separating objects, filling gaps, and enhancing object boundaries.
How It Works
These operations rely on the interaction between an image and a structuring element (kernel). The operations focus on modifying the geometry of objects based on the shape and size of the structuring element.
Common Morphological Operations
Erosion: Removes pixels on object boundaries, shrinking the objects.
Dilation: Adds pixels to object boundaries, expanding the objects.
Opening: Erosion followed by dilation, used to remove small objects/noise.
Closing: Dilation followed by erosion, used to close small holes/gaps.
Effect
Alters the shape of objects in the image without averaging pixel values; instead, it manipulates the binary or grayscale structure of the image.
Other ressource
You can find demonstration of different image filters using convolution on the website geekosophers.com.