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What Is Image Processing ? A Complete Guide with Best Practices

Last updated on 28th Oct 2022, Artciles, Blog

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    • In this article you will get:
    • 1.What is Digital Image Processing?
    • 2.Characteristics of Digital Image Processing
    • 3.Advantages of Digital Image Processing
    • 4.Applications of Image Processing
    • 5.Fundamental Image Processing Steps
    • 6.Types of Image Processing
    • 7.Conclusion

What is Digital Image Processing (DIP)?

Digital Image Processing (DIP) is a software which is used to manipulate a digital images by use of computer system. It is also used to enhance an images, to get some more important information from it.

For example: Adobe Photoshop, MATLAB, etc.

It is also used in a conversion of signals from the image sensor into a digital images.A certain number of an algorithms are used in image processing.It provides an images in various formats.

Digital Image Processing:Digital Image Processing is the software which is used in an image processing.

For example: A computer graphics, a signals, photography, camera mechanism, pixels, etc.

Digital Image Processing allows users following tasks:

Image sharpening and restoration: The common applications of an Image sharpening and restoration are be zooming, blurring, sharpening, grayscale conversion, edges detecting, Image recognition, and Image retrieval, etc.

Medical field: The common applications of a medical field are Gamma-ray imaging, PET scan, X-Ray Imaging, Medical CT, UV imaging, etc.

Remote sensing: It is process of scanning the earth by use of satellite and acknowledges all the activities of space.

Machine/Robot vision: It works on a vision of robots so that they can see the things, identify them, etc.

Characteristics of a Digital Image Processing

  • It uses a software, and some are free of cost.
  • It provides a clear images.
  • Digital Image Processing do image enhancement to recollect a data through images.
  • It is used widely everywhere in more fields.
  • It reduces complexity of a digital image processing.
  • It is used to support the better experience of life.

Advantages of Digital Image Processing

  • An Image reconstruction (CT, MRI, SPECT, PET).
  • An Image reformatting (Multi-plane, multi-view reconstructions).
  • Fast image storage and also retrieval.
  • Fast and high-quality image distribution.
  • Controlled viewing (windowing, zooming).
Digital Image Processing

Characteristics of a Digital Image Processing

  • It uses a software, and some are free of cost.
  • It provides a clear images.
  • Digital Image Processing do image enhancement to recollect a data through images.
  • It is used widely everywhere in more fields.
  • It reduces complexity of a digital image processing.
  • It is used to support the better experience of life.

Advantages of Digital Image Processing

  • An Image reconstruction (CT, MRI, SPECT, PET).
  • An Image reformatting (Multi-plane, multi-view reconstructions).
  • Fast image storage and also retrieval.
  • Fast and high-quality image distribution.
  • Controlled viewing (windowing, zooming).

Applications of Image Processing

Medical Image Retrieval:

Image processing has been extensively used in a medical research and has enabled more efficient and accurate treatment plans. For example, it can be used for early detection of breast cancer using a sophisticated nodule detection algorithm in a breast scans. Since medical usage calls for more trained image processors, these applications needs significant implementation and evaluation before they can be accepted for use.

Traffic Sensing Technologies:

In case of traffic sensors use a video image processing system or VIPS. This consists of a) image capturing system b) a telecommunication system and c) image processing system.

When capturing video, VIPS has a several detection zones which output an “on” signal whenever a vehicle enters zone, and then output an “off” signal whenever a vehicle exits the detection zone. These detection zones can be set up for the multiple lanes and can be used to sense traffic in a specific station.

Besides this, it can auto record license plate of the vehicle, distinguish a type of vehicle, monitor the speed of the driver on highway and lots more.

Image Reconstruction:

  • Image processing can be used to recover and fill in a missing or corrupt parts of an image.
  • This involves using image processing systems that have been trained by an extensively with the existing photo datasets to create newer versions of old and damaged photos.

Face Detection:

  • One of the most common applications of an image processing that use today is face detection.
  • It follows a deep learning algorithms where the machine is first trained with a specific features of human faces, like the shape of the face, the distance between the eyes, etc.
  • After teaching the machine these human face features, it will start to accept all the objects in an image that resemble a human face.
  • Face detection is the vital tool used in security, biometrics and even filters available on a most social media apps these days.

Fundamental Image Processing Steps

Image Acquisition:Image acquisition is a first step in image processing. This step is also known as a preprocessing in image processing. It involves the retrieving the image from a source, usually a hardware-based source.

Image Enhancement:Image enhancement is a process of bringing out and highlighting certain features of interest in image that has been obscured.This can involve changing brightness, contrast, etc.

Image Restoration:Image restoration is a process of improving the appearance of image. However, unlike an image enhancement, image restoration is done using certain mathematical or a probabilistic models.

Color Image Processing:Color image processing included a number of color modeling techniques in the digital domain. This step has gained prominence due to the significant use of a digital images over an internet.

Wavelets and Multiresolution Processing:Wavelets are used to represent a images in different degrees of resolution. The images are subdivided into the wavelets or smaller regions for data compression and for a pyramidal representation.

Compression:Compression is the process used to reduce storage required to save an image or bandwidth required to transmit it. This is done particularly when an image is for use on Internet.

Morphological Processing:Morphological processing is the set of processing operations for the morphing images based on their shapes.

Segmentation:Segmentation is one of most complex steps of image processing. It involves a partitioning an image into its constituent parts or objects.

Representation and Description:

After an image is segmented into the regions in the segmentation process, every region is represented and described in a form suitable for further computer processing.

Representation deals with an image’s characteristics and regional properties. Description deals with the extracting quantitative information that helps differentiate one class of objects from other.

Recognition:Recognition assigns the label to an object based on its description.

Fundamental of Image Processing

Types of Image Processing

Visualization: Find objects that are not visible in an image.

Recognition: Distinguish or detect objects in an image.

Sharpening and restoration: Create an enhanced image from a original image.

Pattern recognition: Measure the different patterns around the objects in the image.

Retrieval :Browse and search an images from a large database of digital images that are similar to a original image.

Conclusion

Digital Image Processing offers a platform to perform various operations like image enhancing, processing of the analog and digital signals, image signals, voice signals etc.

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