In a typical digital image processing system, the source of the image is usually visible light reflected from or transmitted through various objects in a scene. Optics gathers and focuses this light into a sensor that puts an electronic signal to the received light. Images can also be formed using other sources of radiation such as infrared or ultraviolet light, X-rays, radar, or sonar. Images can be synthesized from spatial data by other means, including scanning and computer-aided tomography.

The sensor signal is "digitized"--converted to an array of numerical values, each value representing the light intensity of a small area of the scene. The digitized values are called picture elements, or "pixels," and are stored in computer memory as a digital image. The limited range and number of pixels means that the digital image is only an approximate of the light inte

Image compression reduces the amount of information required to store or transmit a digital image. Compression is called "losses" when the original digital image can be exactly reconstructed from the compressed image. It is called "lossy" when information is lost and the original image can be only approximately reconstructed. Because pixel values often similar to or used with adjacent pixel values, an image can be compressed by removing these correlations.

Another enhancement technique assigns colors to pixel intensities, and thus makes small intensity differences more obvious to the human eye. Color could be used, for example, to highlight details in an X-ray image. Image-enhancement operations are often used in image-processing algorithms, and are used in some digital television sets to improve the visual quality of the received picture.

Image-recognition algorithms attempt automatically to find and identify parts or objects within an image. Typical recognition tasks are not this simple, and often require finding and recognizing objects in cluttered and degraded images. One recognition method compares images of the objects with every area of a sample image. If a template matches some area of the sample image, the image might contain the corresponding object. Unfortunately, the match is usually imperfect due to image noise, object variation, object rotation, changes in lighting, and other factors and so statistical methods are used to decide if the match is valid.

Some topics in this essay:
Scans Images, RECOGNITION Image, RESTORATION Image, EDITING Image, COMPRESSION Image, X-rays CAT, John Kennedy’s, digital image, image processing, image enhancement, image image, image compression, values image, image editing, image analysis, light intensity scene, various objects, human vision, image enhancement restoration,