Have you ever wondered how your smartphone camera applies precise filters to your image?
You might not be surprised to learn that it is all because of technology.
Technology is becoming an integral part of our daily lives in this digital era where artificial intelligence (AI) is paving the way for the journey to a more futuristic world.
So, all the filters you see on your images have artificial intelligence- the protagonist behind image processing.
Not just this, artificial intelligence is entirely altering the way we see the world. It is exponentially becoming a trend in the business world, helping accomplish most image processing tasks.
So, how does AI enable computers, smartphones, or other devices to process images?
You will get the answer to this question once you know what image processing is:
What Is Image Processing?
First things first, it all starts with Computer Vision which enables computer systems to see, process, and make sense of visual data. So, image processing is a subset of it. It simply means computer vision uses image processing algorithms to perform visual analysis.
Generally, image processing refers to manipulating images to enhance or extract information from them. Once a computer (or a smartphone camera) captures images, image processing comes into action. It enhances the images to prepare them for later use.
This is where artificial intelligence truly shines.
What Is The Role Of Artificial Intelligence In Image Processing?
Image processing is one of the most accessible applications of AI for industries that deal with image data computation to achieve meaningful results from visual data.
Just after capturing an image, AI combines with image processing. It leverages deep learning models and involves a complete cycle of operations- from data acquisition to mixing the developed AI model with the end results.
The use of AI models accelerates data processing and boosts the quality of final results.
For example, artificial intelligence platforms can successfully perform complex tasks like face recognition and object detection.
What Are The Main Purposes Of Image Processing?
Since we live in digital age, everything we find around us is connected to a data source. Similarly, to make sense of digital or analog images, we need insight into visuals to understand what they represent. That is why the concept of image processing has developed.
Today, image processing is used to accomplish the following purposes:
Image Sharpening and Restoration
Image quality improves once images are processed, such as better picture quality after applying a filter.
AI-powered image processing represents visual data in an understandable format. If some objects in an image are not visible, they are processed and given a visual form.
This process also measures the objects in an image by figuring out size, shape, etc.
By identifying positions and understanding the scenes, image processing uses AI to distinguish and classify objects in an image.
What Are Real-Life Applications Of Image Processing?
With AI giving image processing a new way to accomplish every simple to a complex task, it exhibits plenty of uses in various industries.
Some industries where image processing is more common include:
Image processing has strengthened medical technology and eminently improved the diagnostic process.
In the medical field, AI combined with image processing assists in various tasks like X-Ray Imaging, PET scan, Medical CT, Cancer Cell Image Processing, UV imaging, and more.
One of the most interesting applications of image processing is in the transportation sector. While computer vision enables self-driving cars and drones to move autonomously, the image processing helps detect obstacles, recognize paths, and understand the environment.
To Sum Up
Image processing is not merely a feature of your camera but the manifestation of artificial intelligence models behind it.
With its ability to crack a great number of visual data problems, image processing has become the key to driving most of the business world tasks.
In this process, AI goes hand in hand with image processing to make visual interpretation more efficient and accurate.