When we convert an image into a digital file, make edits to it, or analyze it to gain certain information, we are performing image processing. In every case, the image is the input signal, and the output signal may be an edited version of the image, or data gathered from it. There are a variety of objectives to image processing, and it can be performed in computer science, photography, medicine, and many other fields. Below, we’ve outlined the basic steps behind image processing, and how it can be used for restoration, recognition, and deeper analysis.
What is Image Processing?
In today’s fast-paced digital world, image processing can be used for research, business, and creative purposes in almost any discipline. Here are three essential steps that allow users to manipulate an image:
- Import: First, you must scan a physical image into the computer, or upload a digital file using a cable connection.
- Edit: Once the image is loaded, specialty computer software can analyze and edit the data. Depending on your goals, there are programs that can enhance, compress, and study images on a microscopic level.
- Export: When the software completes its task, you will receive a processed image file, or an analytical report about the image.
What Can Image Processing Achieve?
Here are some of the most common applications for image processing:
- Restoration: When an image is noisy and riddled with artifacts, editors can use image processing to gauge what the original image looked like, and then restore it to a clean state. To achieve this, computer tools can reverse-engineer the process that corrupted the image in the first place, and then try to repair the damaged areas. Unlike image enhancement, restoration is only used to achieve realistic results, so that the image looks as accurate as possible.
- Recognition: Also known as computer vision, scientists have been trying to teach computers how to recognize images at a glance. When we look at pictures of a ship or a toy boat, we can recognize and distinguish between them instantly, but this is not as easy for a computer. However, the latest algorithms have gotten much faster, and today’s programs can accurately describe image content.
- Analysis: Processing can also be used to analyze images, collect data, and search for specific details. This might be as simple as counting items on a conveyor belt, or as sophisticated as alerting workers when a heavy-duty tool has worn down. Image processing can be used to locate cancer cells, keep self-driving cars on the road, and much more.