Most of the signal processing concepts that apply to one-dimensional signals — such as resolution, dynamic range, bandwidth, filtering, etc. — extend naturally to images as well. However, image processing brings some new concepts — such as connectivity and rotational invariance — that are meaningful or useful only for two-dimensional signals. Also, certain one-dimensional concepts — such as differential operators, edge detection, and domain modulation — become substantially more complicated when extended to two dimensions.
A few decades ago, image processing was done largely in the analog domain, chiefly by optical devices. Optical methods are inherently parallel, and for that reason they are still essential to holography and a few other applications. However, as computers keep getting faster, analog techniques are being increasingly replaced by digital image processing techniques — which are more versatile, reliable, accurate, and easier to implement.