Neighbourhood pixels in image processing

The neighbourhood of a pixel is the collection of pixels which surround it. The neighbourhood of a pixel is required for operations such as morphology, edge detection, median filter, etc. Many computer vision algorithms allow the programmer to choose an arbitrary neighborhood.

1. What is neighborhood in image processing?
2. What are different types of neighborhoods of a pixel in an image?
3. What do you mean by 4-neighbors of pixel?
4. What is the difference between 4 and 8 neighborhood pixels?

What is neighborhood in image processing?

Certain image processing operations involve processing an image in sections, called blocks or neighborhoods, rather than processing the entire image at once. Several functions in the toolbox, such as linear filtering and morphological functions, use this approach.

What are different types of neighborhoods of a pixel in an image?

A pixel p at (x,y) has 4-horizontal/vertical neighbours at (x+1,y), (x-1,y), (x,y+1) and (x,y-1). These are called the 4-neighbours of p : N4(p). A pixel p at (x,y) has 4 diagonal neighbours at (x+1,y+1), (x+1,y-1), (x-1,y+1) and (x-1,y-1). These are called the diagonal-neighbours of p : ND(p).

What do you mean by 4-neighbors of pixel?

For a pixel p with the coordinates (x,y) the set of pixels given by: is called its 4-neighbors. Its 8-neighbors are defined as From this we can infer the definition for 4- and 8-connectivity: Two pixels p and q, both having values from a set V are 4-connected if q is from the set and 8-connected if q is from .

What is the difference between 4 and 8 neighborhood pixels?

In an 8 neighbour configuration, the spatial distances between the central pixel and its neighbours are not all equal, unlike in the 4 neighbour configuration. I took this into account by multiplying the incremental "cost" value between two pixels by the Euclidean length of their spatial separation.