Digital Image Processing and its applications

What is digital image processing?

As evident from the question, digital image processing is the processing of images that are digitally stored using a computer. In other words, we can say that “Digital Image Processing refers to the processing of digital images by means of a digital computer.

Now that we have understood that what is digital image processing, let us understand that what do we mean by the digital image. Before understanding about a digital image, let us see first that what is an image.

An image can be defined as a function f(x,y). Here

  • x and y are spatial (plane) coordinates.
  • the amplitude of function at any point (x,y) is called intensity or grey level of an image at that point.

Now an image is said to be a digital image when x,y and amplitude values of function f(x,y) are finite and discrete in nature.

A digital image is composed of a finite number of elements (known as pixels), each of which has

  • a particular value
  • a particular location

A pixel is the smallest element in an image.

Three levels of processing in digital image processing:

In general, there are three levels of processing or three types of processes in digital image processing namely: low, mid and high-level processes.

  • Low-level processing involves primitive operation such as image preprocessing to reduce noise, contrast enhancement, image sharpening, etc. In the low-level process, both input and output are images.
  • Mid-level processing involves tasks such as image segmentation, description of images, object recognition, etc. In the mid-level process, inputs are generally images but its outputs are generally image attributes.
  • High-level processing involves “making sense” from a group of recognized objects. This process is normally associated with computer vision.

Applications of digital image processing:

  1. Automatic character recognition.
  2. Military recognition.
  3. Automatic processing of fingerprints.
  4. Screening of X-ray and blood samples.
  5. It is used in the study of pollution particles.
  6. It is used to restore blurred pictures of rare artifacts (application in archaeology).
  7. Industrial machine vision for products assembly and inspection.
  8. Machine processing of aerial and satellite imagery for weather prediction.
  9. In astronomy, biology, nuclear medicine, law enforcement, defence and industry, etc.

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