Image processing and it's role in remote sensing

Content

  1. Introduction
  2. API concept
  3. FastApi
  4. JSON: JavaScript Object Notation
  5. Reference

Introduction

Image processing is a technique employed to execute various operations on an image with the aim of obtaining an improved image or extracting valuable information from it. It falls under the domain of signal processing, where the input is an image, and the output can be either an image or characteristics/features related to that image. In contemporary times, image processing stands as one of the swiftly advancing technologies, constituting a fundamental research area within the fields of engineering and computer science.

Image processing basically includes the following three steps:

  • Importing the image via image acquisition tools;
  • Analysing and manipulating the image;
  • Output in which result can be altered image or report that is based on image analysis.
There are two types of methods used for image processing namely, analogue and digital image processing. Analogue image processing can be used for the hard copies like printouts and photographs. Image analysts use various fundamentals of interpretation while using these visual techniques. Digital image processing techniques help in manipulation of the digital images by using computers. The three general phases that all types of data have to undergo while using digital technique are pre-processing, enhancement, and display, information extraction.

Applications of image processing

Image processing has a wide range of applications in many different fields. Some of the most common applications include:
  • Medical imaging: Image processing is used in a variety of medical imaging techniques, such as X-rays, MRIs, and CT scans.
  • Machine vision: Image processing is used in machine vision systems to identify and track objects.
  • Digital art: Image processing is used to create a variety of digital art effects, such as filters and textures.
  • Security: Image processing is used in security systems to detect and identify objects, such as faces and license plates
  • Scientific research: Image processing is used in a variety of scientific research applications, such as astronomy and biology.
  • Remote sensing:Image processing plays a crucial role in remote sensing, enabling the extraction of valuable information from satellite and airborne imagery.

Common image processing tasks

  • Image enhancement: This involves improving the quality of an image, such as by increasing its contrast or sharpness.
  • Image restoration: This involves removing noise or artifacts from an image.
  • Image segmentation: This involves dividing an image into different regions based on their properties, such as color or texture.
  • Object detection: This involves finding and identifying objects in an image.
  • Image classification: This involves assigning labels to images based on their content.

Image processing techniques

There are many different techniques that can be used for image processing. Some of the most common techniques include:
  • Filtering: This involves applying a mathematical operation to each pixel in an image to modify its value (check out).
  • Morphological operations: These operations are based on the shape and size of objects in an image
  • Feature extraction: This involves extracting information from an image that can be used to identify objects or classify images (check out).
  • Pattern recognition: This involves using algorithms to identify patterns in data, such as images.

References

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