The value of the function determines the intensity or gray level of the image at that point. Image courtesy of The Scientist and Engineer's Guide to Digital Signal Processing.īased on the above discussion, we can represent a grayscale image as a two-dimensional function I where the arguments x and y are the plane coordinates that specify a particular pixel of the image. Figure 1 shows a portion of a grayscale image along with its corresponding pixel values.įigure 1. The intermediate values correspond to the different shades of gray. ![]() In this case, the value of each pixel can vary from 0 that represents black to 255 that relates to white. For example, a grayscale image may use 8 bits to represent the value of a pixel. One common method to represent a digital image is to store each pixel value as an unsigned N-bit number. In fact, the different bands of the electromagnetic spectrum can be used to glean the fullest possible amount of information from the world around us. It’s important to note that the radiation doesn’t have to be from the visible light band. The value of each pixel relates to the energy that our imaging device receives from the source of radiation. For example, many commercially available imaging devices produce images of approximately 512 x 512 pixels. Then, we’ll discuss some simple operations that allow us to adjust the brightness and contrast of an image.įinally, we’ll briefly look at the circuit implementation of these operations.Ī digital image can be described by a two-dimensional array of small elements called pixels (a contraction of the phrase picture elements). ![]() In this article, we’ll first look at the basics of representing a digital image. Digital image processing involves developing algorithms that can be used to enhance a given image or extract some useful information from it.
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