One of the first applications of digital images was digitized newspaper pictures sent by submarine cable between London and New York. Introduction of the Bartlane cable picture transmission system in the early 1920's reduced the time required to transport a picture across the Atlantic from more than a week to less than three hours. Pictures were coded for cable transmission and then reconstructed at the receiving end on a telegraph printer fitted with type faces simulating a halftone pattern. The early Bartlane systems were capable of coding images in five distinct brightness levels. This was increased to fifteen levels in 1929.

Although improvements on methods for transmitted digital pictures continued to be made over the next thirty-five years, it took the combined advents of large-scale digital computers and the space program to bring into focus the potentials of digital image concepts. Work on using computer techniques for improving images from a space probe began at the Jet Propulsion Laboratory in 1964, when pictures of the Moon transmitted by Ranger 7 were processed by a computer to correct various types of image distortion inherent in the on-board television camera. These techniques served as the basis for improved methods used in the enhancement and restoration of images from such familiar programs as the Surveyor missions to the Moon and the Mariner series of flyby missions to Mars.

In addition to applications in the space program, digital image processing techniques are used today in a variety of problems which, although often unrelated, share a common need for methods capable of enhancing pictorial information for human interpretation and analysis.

In medicine, for instance, physicians are assisted by computer procedures that enhance the contrast or code the intensity levels into color for easier interpretation of x-rays and other biomedical images. Similar techniques are used by geographers in studying pollution patterns from aerial and satellite imagery. Image enhancement and restoration procedures have been used to process degraded images depicting unrecoverable objects or experimental results too expensive to duplicate. There have been instances in archeology, for example, where blurred pictures which were the only available records of rare artifacts lost or damaged after being photographed, have been successfully restored by image processing methods. In physics and related fields, images of experiments in such areas as high-energy plasmas and electron microscopy are routinely enhanced by computer techniques. Similar successful applications of image processing concepts can be found in astronomy, biology, nuclear medicine, law enforcement, defense, and industrial applications.

These examples have in common the fact that processing results are intended for human interpretation. The second major application area of digital image processing techniques is in problems dealing with machine perception. In this case, interest is focused on procedures for extracting from an image information in a form suitable for computer processing. Often, this information bears little resemblance to visual features used by humans in interpreting the content of an image. Examples of the type of information used in machine perception are statistical moments, Fourier transform coefficients, and multidimensional distance measures.

Typical problems in machine perception which routinely employ image processing techniques are automatic character recognition, industrial robots for product assembly and inspection, military recognizance, automatic processing of fingerprints, screening of x-rays and blood samples, and machine processing of aerial and satellite imagery for weather prediction and crop assessment.

Digital Image Representation

The term monochrome image or simply image, refers to a two-dimensional light intensity function f(x,y), where x and y denote spatial coordinates and the value of f at any point (x, y) is proportional to the brightness (or gray level) of the image at that point. The x axis is usually the horizontal axis. The x axis is usually the vertical axis. The origin of the coordinate system is usually the upper left corner of the image. The x axis is positive from left to right. The y axis is positive from the top to the bottom of the image.

A digital image is an image f(x,y) which has been discretized both in spatial coordinates and in brightness. We may consider a digital image as a matrix whose row and column indices identify a point in the image and the corresponding matrix element value identifies the gray level at that point. The elements of such a digital array are called image elements, picture elements, pixels, or pels, with the last two names being commonly used.

Digitizers