What is the term for this image processing?

In summary, the process of simplifying an image by reducing the amount of pixels is known as downsampling or rescaling. This process can also involve interpolation, which is needed for both upsampling and downsampling. Other terms that could be used to describe this process include coarsening, compression, and scaling. However, downsampling is the most accurate term for this specific type of digital image processing.
  • #1
Jun Kyoto
14
1
How do you call of the digital image processing that simplifies an image by reducing the amount of pixels?

I thought of the word “thinning”. But according to ”Fundamentals of Digital Image Processing” by Anil K. Jain, “Thinning algorithm transforms an object to a set of simple digital arcs, which lie roughly along their medial axes” while the processing I am searching a term has nothing to do with medial axes. Instead, it eliminates pixels in a consistent balance (e.g,.one pixel in every three pixels).

Any suggestion/ insight will be much appreciated.
Also, are “simple digital arcs” in the quote equivalent to edges?

Thank you in advance.
 
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  • #2
A few terms come to mind: coarsening, rescaling, or interpolating. Don't quote me though.
 
  • #3
How about "compression"?
 
  • #4
phyzguy said:
How about "compression"?

That was the first thing that came to my mind, but I think that has to do with storing the file on disk more efficiently. I think the process we are describing might be considered a type of compression, but not all compression is rescaling. For instance, some compression is lossless.
 
  • #5
How about "downsampling"? For an image, it would only take the Nth pixel in a group of pixels, but that seems not to be what you're after since it seems you're trying to simplify the semantic image, not just the raw number of pixels.
 
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  • #6
It is "resolution". if you reduce the number of pixels you reduce the resolution.

Resolution is determined by the size of the units of information representing an image. A pixel is a unit of information displayed on a monitor. Each pixel holds a defined amount of information stored on your disk. An image of a given area will become more detailed as more pixels are used to describe it.
http://jura.wi.mit.edu/bio/graphics/scanning/resolution.php
 
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  • #7
The catch all term for images in general (including vector images) is "scaling". For scaling bitmaps (raster) the process is called "resampling", going from low resolution to high resolution is "upsampling" while going from a high resolution to a low resolution is called "downsampling".
 
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  • #8
Thank you everyone! I think "downsampling" is it. Just to understand further, interpolating is a method for upsampling, am I right?
timthereaper said:
How about "downsampling"? For an image, it would only take the Nth pixel in a group of pixels, but that seems not to be what you're after since it seems you're trying to simplify the semantic image, not just the raw number of pixels.
>
I was trying to simplify an image by reducing just the raw number of pixels.
 
  • #9
Jun Kyoto said:
interpolating is a method for upsampling

Interpolation is also needed for downsampling. For example, consider downsampling an image from 1000 x 1000 pixels to 700 x 700. If the pixels are to remain evenly distributed, the centers of most of the new pixels cannot be at the same locations as the centers of the old pixels, so they have to be interpolated from the old pixels.
 
  • #10
The term is downsampling " Downsampling is the process by which a high-resolution image is transformed into a lower resolution image."
 
  • #11
I think it's rescaling the image to a smaller size that is to transform your image from one size to another. By this, the number of pixels gets reduced.
 

Related to What is the term for this image processing?

1. What is image processing?

Image processing is the manipulation of images using computer algorithms and software. It involves techniques for enhancing, analyzing, and converting visual information from an image for better understanding and use.

2. What are the different types of image processing?

The different types of image processing include image enhancement, image restoration, image analysis, and image compression. Image enhancement involves improving the visual quality of an image. Image restoration aims to remove noise or distortions from an image. Image analysis involves extracting information from an image for further processing. Image compression reduces the size of an image for storage and transmission purposes.

3. How is image processing used in science?

Image processing is used in various scientific fields, including medical imaging, remote sensing, and astronomy. In medical imaging, it is used for diagnosis and treatment of diseases. In remote sensing, it is used for analyzing satellite images to study the Earth's surface. In astronomy, it is used for processing images captured by telescopes to study celestial objects.

4. What is the difference between image processing and computer vision?

Image processing deals with processing and manipulating images, while computer vision involves the extraction of information and understanding from images. In other words, image processing focuses on the technical aspects of images, while computer vision focuses on the interpretation and analysis of images to mimic human vision.

5. What are the main challenges in image processing?

The main challenges in image processing include dealing with noise and distortions in images, handling large amounts of data, and developing algorithms that can efficiently process images in real-time. Other challenges include developing methods for image segmentation, object recognition, and creating algorithms that can work with diverse types of images.

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