Deconvolution removes signal degradation from recorded data caused by convolution, which can be from incorrect recording or interference during transmission. It is used in signal processing, audio and video processing, and seismology. The process involves determining the convolution and applying an opposite convolution to cancel it out. Deconvolution is used to correct optical images, improve signal strength, and learn about the point of origin of a signal in seismology.
Deconvolution is the process of removing signal degradation from recorded data. Signals have two main ways of being damaged: either the signal is created or recorded incorrectly, or the signal is interfered with as it travels from one point to another. Any form of damage to the signal is called a convolution, and deconvolution is the process of eliminating such convolutions without harming the original data. These processes are used extensively in signal processing, audio and video processing, and seismology, but the underlying process is used in nearly every mainstream science.
Any break in a signal is a convolution. It doesn’t matter if the interruption is caused by another signal, a reflection of the original or even a faulty recording device. Small convolutions usually don’t interrupt the signal enough to worry; these are often predicted simply by the signal moving through space. On the other hand, large convolutions will render a signal unreadable and will need to be removed.
The vast majority of deconvolution is determining what convolutions happened to the original signal. Once the exact convolution is determined, the original can be edited to eliminate it. Most of the time, this simply means that the signal is changed again by another convolution that is exactly opposite to 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 for correcting optical images to account for magnification distortion. When a lens magnifies an image, the image is not magnified uniformly over the entire field. Even in high-end microscopes and telescopes, there is a very small amount of distortion. When an image is greatly magnified, looking at a very small or very distant object, the distortion can radically affect the image. By applying an opposite convolution to the image, a much truer version is created.
This same technique is used in many other audio and visual fields to improve signal strength and create more lifelike recordings. In seismology, a signal is distorted by distance, medium and reflections from itself. All these convolutions amount to an almost useless signal. By using deconvolution to move backwards through all the distortions, scientists can learn more about what is happening at the point of origin of the signal and what kinds of things exist between the transmission and reception of the signal.
Protect your devices with Threat Protection by NordVPN
