Digital Image Processing relates to a process that involves the conversion of an image into its digital format. After that, technicians also perform different operations on the processed image.
This is a way to get an enhanced and clear image. It is also used to extract useful information out of the image. The image processing is similar to signal dispensation.
Here, the input is the image, video, or photograph. The output can be a refined image or other characteristics of such an image.
Normally, the procedure of image processing treats images as two-dimensional signals. This is done after applying signal-processing methods to such images.
There are five major purposes associated with image processing. These include:
1. Offers a clear image to observe, which isn’t visible without the image process.
2. Image processing ensures complete restoration and sharpening of the image. Hence, it helps to create a refined image.
3. It helps to retrieve an image that is of great importance.
4. This process makes it possible to measure different objects in a particular image.
5. The image processing also recognizes and distinguishes a specific object in the image.
Listed below are the different applications of image processing:
1. Face detection
2. Fingerprint sensor
3. License plate identification
4. Iris recognition
All these applications of image processing rely on an image produced by a digital camera or scanner. The image thus captured is converted into a digital file like JPEG.
When processing images in a video, the video data undergoes a decoding procedure. This creates video frames or full-scale images for better visualization.
Listed below are the steps associated with video processing.
This step involves acquiring an image in digital form. Usually, the image thus acquired passes through different steps such as scaling.
It is one of the simplest procedures linked with image processing. This process helps to clarify details that are obscured. It helps to highlight specific features that contain necessary information.
Image restoration tends to improve the overall appearance of an image. The restoration techniques rely on probabilistic or mathematical models.
Wavelets offer multiple resolutions of an image. The subdivision of images into relatively smaller parts helps during data compression. This in turn allows pyramidal representation.
This process includes techniques for minimizing the size of the image. This helps to transfer the image much quickly via the internet.
It deals with the extraction of image components. These are necessary for the description and representation of shape.
Segmentation relates to the partition of a specific image into different segments and parts. Usually, this is among the most difficult tasks associated with image processing.
This process includes labeling an object in an image. The object is located in the image through its descriptors.
It is a task of detailing regions of the image. The relevant information is located, which helps to limit the search.