Overview of Digital Image Processing

Overview of Digital Image Processing

Image Description
Input Image image processing computer vision
image analysis
Description computer graphics
image synthesis
information processing

Computer vision goes by many aliases: machine vision, image analysis, image understanding, and computational vision. Each has its own connotation and is used by different parts of the community. Traditionally computer vision and machine vision imply endowing a computer or other machine with visual capabilities, suggesting robotics and other autonomous computer-guided devices. Image analysis and image understanding generally refer to figuring out the content of images -- a part of computer vision but without the implication of the computer having immediate access to live video (seeing). Computational vision is starting to gain favor as a term that refers to modelling visual processes by computational means.

Digital Image Fundamentals



Image Model


Image Composition

Image Composition refers to the creation of new images.

Digitization, scanning, sampling
Converting pictures to discrete (digital) form
Digital reconstruction images from its projections. Examples include Computerized tomography, ultrasonic imaging, nuclear medicine.
Computer Graphics
software whose output is an image

  • text editing programs (page composition)
  • paint programs
  • page layout
  • compositing, overlaying images from several different sources

Image Enhancement

Ehancement is the process of transforming pictures to improve the appearance of the image for a specific application.

Point Processing

Point operations take a single pixel of the source image and returning a single pixel to the destination image. Other names include contrast enhancement, contrast stretching, gray scale manipulation.

Algebraic operations produce an output image that is the pixel-by-pixel result of combined algebraic operations of two or more input images to produce a single output image.

Geometrical Operations

Geometric operations change the spatial relationship among pixels. Define a mapping or spatial transformation of pixel positions. The effect is that of printing image on rubber sheet and topoglogically transforming the sheet.

Geometrical operations change the position of pixels in the image, presumably without changing the value of the pixels.

Neighborhood Operations (Filtering in Spatial Domain)

Local operations change the value of a pixel based on value of neighboring pixels. (Spatial convolution or other neighborhood processing operations)

Transform Operations (Filtering in Frequency Domain)

Global operations are those in which the value of any pixel could affect the value of any other pixel.

Image Restoration

Restoration is the process of transforming pictures that have been recorded in the prescence of one or more known sources of degradation to eliminate the effects of the degradation.


Segmentation is the process of partitioning image space into meaningful regions.

Image Analysis

Image analysis is the extraction of useful measurements, data, or information from an image. Determining image content.

A knowledge base is the itemization and interrelationships between elements of one or more pictures. Image hierarchy. Semantic net.

Inferences. Expert systems.

Image Compression

Compression is a reduction in the number of bits required to represent an image. Encoding is the process of creating a compressed image, decoding the process of regenerating the original image. Some encoding techniques allow perfect decoding. The original image may be recovered exactly (information preserving). Other techniques result in some loss of image fidelty.

Maintained by John Loomis, last updated May 8, 1997