Image processing is an important concept to learn about, especially for anyone looking to keep an eye on technological changes. Digital image processing has inserted itself into a lot of different fields. Use this guide to get a firm grasp on the topic.
What Is Image Processing?
Image processing is the handling and development of an image using different measurement factors, including object detection. Digital image processing applies mathematical algorithms to an image to evaluate and change its characteristics like contrast. Digital processing has been applied to both film and digital camera photos.
Note that image processing is different from image editing, which addresses the image from an artistic standpoint. Image editing does things like change colors, styles and layouts of graphics. Image processing is a more technical type of alteration, changing things such as deteriorating graphics.
What Are the Different Types of Image?
Also known as the binary image, it is made up of 2 pixel values, 0 and 1. In monochrome, zero represents black and one represents white.
The 8-bit image is the most commonly-used format. It is made up of 256 color shades, where zero represents black and 255 represents white. It is also known as a grayscale image.
The 16-bit image deals with colors, differing between specific color formats. Its color distribution scale is much different than the 8-bit format.
Image Processing in Action
The following are examples of image processing applications. These aren’t the only applications, however, they do represent a large portion of the most popular and important ones.
Strange as it may seem, one of the applications of digital image processing is video processing. This is because videos are made up of a collection of singular images, pieced together quickly to create moving images. Image processing involves motion detection of these videos.
Image sharpening is the transformation of the sensory aspect of an image. It is the alteration of images to create a specific wanted outcome. This application involves things such as blurring and edge-detection.
Within the medical field, there are plenty of different procedures and operations that involve image processing. For example, things such as x-rays and CT scans both rely on extensive image processing.
Pattern recognition is machine learning that uses data to discover patterns and other regularities. Image processing is used to supplement and bolster any pattern recognition efforts.
Robotic creations function based on digital image processing. For example, a robot navigates a room by using image processing to guide itself.
As you can see, image processing is prevalent in our daily lives. Even as technology changes, image processing – especially digital image processing – evolves with it. In order to understand what the future of technology will bring, begin by understanding things like image processing.