Digital Image Representation
An image can be defined as a two-dimensional function f(x, y), where x and y are spatial (plane) coordinates and the amplitude of f at any point (x, y) is called the intensity of the image at that point. The term gray level is used to refer the intensity of monochrome images. Color images are formed by a combination of individual 2-D images. For example, in the RGB color system, a color image consists of three (red, green, and blue) individual component images.
An image may be continuous with respect to the x and y-coordinates, and also in amplitude. Converting such an image to digital form requires that the coordinates as well as amplitude, be digitized. Digitizing the coordinate values is called sampling; digitizing the amplitude values is called quantization. Thus, when x, y, and the amplitude values of f are all finite, discrete quantities, we call the image a digital image.
Examples of digital images are:
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Digital photographs
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Satellite images
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Radiological images (x-rays, mammograms)
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Binary images, fax images, engineering drawings
Sampling and Quantization
To create a digital image, we need to convert the continuous sensed data into digital form. This involves two processes: sampling and quantization. A continuous image, f(x, y), that we want to convert to digital form. An image may be continuous with respect to the x- and y-coordinates, and also in amplitude. To convert it to digital form, we have to sample the function in both coordinates and in amplitude.
Digitizing the coordinate values is called Sampling.
Digitizing the amplitude values is called Quantization.
Figure: Analog Image and Digital Image
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