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techniques to the domain of images — two-dimensional signals such as photographs or video.
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 parallelThe term Parallel has a number of important meanings: Parallel (geometry) occurs in geometry. If two lines or planes are parallel, then every point on one is located exactly the same minimum distance from the other line or plane. A parallel is a circle of, and for that reason they are still essential to holographyTraditionally, a holograph is a document written entirely in the handwriting of the person whose signature it bears. That is not what this article is about; this is about the more modern concept, not introduced until the 20th century. This article is also and a few other applications. However, as computers keep getting faster, analog techniques are being increasingly replaced by digital image processingDigital image processing is the study of algorithms applied to digital images. Typical problems covered by this field include geometric transformations such as enlargement, reduction, and rotation; color corrections such as brightness and contrast adjustm techniques — which are more versatile, reliable, accurate, and easier to implement.