We are independent & ad-supported. We may earn a commission for purchases made through our links.
Advertiser Disclosure
Our website is an independent, advertising-supported platform. We provide our content free of charge to our readers, and to keep it that way, we rely on revenue generated through advertisements and affiliate partnerships. This means that when you click on certain links on our site and make a purchase, we may earn a commission. Learn more.
How We Make Money
We sustain our operations through affiliate commissions and advertising. If you click on an affiliate link and make a purchase, we may receive a commission from the merchant at no additional cost to you. We also display advertisements on our website, which help generate revenue to support our work and keep our content free for readers. Our editorial team operates independently of our advertising and affiliate partnerships to ensure that our content remains unbiased and focused on providing you with the best information and recommendations based on thorough research and honest evaluations. To remain transparent, we’ve provided a list of our current affiliate partners here.

Our Promise to you

Founded in 2002, our company has been a trusted resource for readers seeking informative and engaging content. Our dedication to quality remains unwavering—and will never change. We follow a strict editorial policy, ensuring that our content is authored by highly qualified professionals and edited by subject matter experts. This guarantees that everything we publish is objective, accurate, and trustworthy.

Over the years, we've refined our approach to cover a wide range of topics, providing readers with reliable and practical advice to enhance their knowledge and skills. That's why millions of readers turn to us each year. Join us in celebrating the joy of learning, guided by standards you can trust.

What Is Deconvolution?

M. McGee
Updated: May 21, 2024

Deconvolution is the process of removing signal degradation from recorded data. Signals have two primary ways of being damaged: either the signal is created or recorded incorrectly or the signal is interfered with as it travels from point to point. Any form of signal damage is called a convolution and deconvolution is the process of taking those convolutions out without damaging the original data. These processes are used heavily in signal processing, audio and video processing and seismology, but the underlying process is used in nearly all mainstream sciences.

Any disruption to a signal is a convolution. It doesn’t matter if the disruption is caused by another signal, a reflection of the original or even a faulty recording device. Small convolutions usually don’t disrupt the signal enough to worry about; these are often expected simply from the signal moving through space. On the other hand, large convolutions will make a signal unreadable and need to be removed.

The vast majority of deconvolution is determining what convolutions happened to the original signal. Once the exact convolution is determined, it is possible to modify the original to edit it out. The majority of the time, this simply means the signal is modified again by another convolution that is exactly opposite of the original disruptor. These two signals will cancel each other out and return the recorded information to its original form.

This process has a huge number of real world applications. Deconvolution is widely used as a method of correcting optical images to account for magnification distortion. When a lens magnifies an image, the image isn’t magnified evenly across the entire field. Even in high-end microscopes and telescopes, there is a very small amount of distortion. When an image is heavily magnified, either by looking at a very small or a very distant object, the distortion can radically affect the image. By applying an opposing convolution to the image, a much truer version is created.

This same technique is used in several other audio and visual fields to improve the signal strength and create more real recordings. In seismology, a signal is distorted by distance, medium and reflections of itself. All of these convolutions amount to a nearly useless signal. By using deconvolution to move backward through all of the distortions, scientists can learn more about what is happening at the point of the signal’s origin and what sorts of things exist between signal transmission and receiving.

All The Science is dedicated to providing accurate and trustworthy information. We carefully select reputable sources and employ a rigorous fact-checking process to maintain the highest standards. To learn more about our commitment to accuracy, read our editorial process.
Link to Sources
M. McGee
By M. McGee
Mark McGee is a skilled writer and communicator who excels in crafting content that resonates with diverse audiences. With a background in communication-related fields, he brings strong organizational and interpersonal skills to his writing, ensuring that his work is both informative and engaging.
Discussion Comments
M. McGee
M. McGee
Mark McGee is a skilled writer and communicator who excels in crafting content that resonates with diverse audiences....
Learn more
All The Science, in your inbox

Our latest articles, guides, and more, delivered daily.

All The Science, in your inbox

Our latest articles, guides, and more, delivered daily.