Spatial Domain

• The term spatial domain means working in. the given, space, in this case, the image. It implies working with the pixel values are in other words, working directly with the raw data.

• Let f(x, y) be the original image where f is the grey level value and (x, y) are the image coordinates. For a 8-bit image, f can take values from 0 - 255 where 0 represents black, 255 represents white and all the intermediate values represent shades grey.

  

  Figure 5

• In image of size , x and y can take values from (0, 0) to (255, 255) as shown in the Figure.6

• The modified image can be expressed as

  $ g (x,y) = T[f(x,y)]$

• Here f(x, y) is the original image and T is the transformation applied to it to get a new modified image g(x, y). For all spatial domain techniques it is simply T that changes. The general equation remains the same.

  $S = T(r)$

  Where S = output gray level; T = Transformation Function; r =input gray level

• To summarize, spatial domain techniques are those, which directly work with the pixel values to get a new image based on Equation above.

• Spatial domain enhancement can be carried out in two different ways

  (1) Point processing

  (2) Neighborhood processing