And as processer capabilities have expanded, newer algorithms are being developed that take advantage of these capabilities. Image processing involves the transformation of a 2D image to its pixel form, and performing certain mathematical operations on it in order to enhance its utility. Each of these discrete elements is called a pixel. A digital image is composed of a finite number of elements, each of which has a particular location and value. When all three (x, y, and f) are finite and discrete quantities, the image generated is called a digital image. The amplitude of f at any pair of x and y co-ordinates is called the intensity or gray level of the image at that point. In mathematical terms, which is the language computers understand, an image is a 2D function f (x, y), where x and y are spatial (planar) co-ordinates. In order to make sense of these pixels, computers need to decipher what the pixels mean, before trying to enhance the image. So, how does digital image processing work? The key in understanding the technology behind DIP is that what the human eye perceives an image – which is a coherent set of data bunched together – is simply a cluster of pixels to computers. Implementing them requires sophisticated math software. There are a number of digital image processing algorithms that exist today to convert such analog images to their digital form, and also for image enhancement, restoration, detection and estimation, reconstruction, data compression, spectral estimation, and analysis.
Just as an example, sampling an image on a 1024 x 1024 grid, where each picture element is quantized to 10 bits, results in a data array of over 10 million bits. The conversion of images from analog to digital involves massive amounts of data. Apart from such use, image processing is also used for pattern recognition, video processing, remote sensing, transmission and encoding, machine / robot vision, radio astronomy, microscopic imaging and many other fields. It is equally useful in military surveillance too. In the automobile sector, image processing is an important part of autonomous driving technology as well enabling AI equipped cars to comprehend ambient surroundings better, even in adverse weather conditions. The introduction of digital image processing (DIP) like X-ray imaging, PET scan, CT scan, helped doctors and surgeons understand the underlying cause better, and helped in improving diagnosis and treatment due to enhanced detailing of the images. The first and foremost field that comes to the mind is the medical sector. It is said that a picture is worth a thousand words, and this adage is true in many fields.
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