Spatial Domain:

• Spatial domain techniques directly deal with image pixels. The pixel values are manipulated to achieve desired enhancement.
• Spatial domain techniques like the logarithmic transforms, power law transforms, histogram equalization are based on direct manipulation of the pixels in the image.
• Spatial techniques are particularly useful for directly altering the gray level values of individual pixels and hence the overall contrast of the entire image. But they usually enhance the whole image in a uniform manner which in many cases produces undesirable results.
• It is not possible to selectively enhance edges or other required information effectively.

Transformation Domain:

• Transformation or frequency domain techniques are based on the manipulation of the orthogonal transform of the image rather than the image itself. Transformation domain techniques are suited for processing the image according to the frequency content.
• The principle behind the frequency domain methods of image enhancement consists of computing a 2D discrete unitary transform of the image.
• The orthogonal transform of the image has two components magnitude and phase. The magnitude consists of the frequency component and phase is used to restore the image back to the spatial domain.
• The transformation enables operation on the frequency content of the image and therefore high frequency content such as edges and other subtle information can be easily enhanced.