The researchers used infrared (IR) imaging and artificial intelligence to convert monochrome night vision images to color. The new system could someday provide color night vision tools for military use, security professionals, and wildlife observers.
At night it's all black (or green)
Human beings see things in the spectrum of visible light, which gives rise to the enormous variety of perceived colors. Night vision technologies mimic this ability by capturing invisible infrared light and converting it into a signal that can be perceived by the human eye. The infrared sensors, however, collect information that limits these images to a monochrome representation only.
Some advances in IR technology have improved things a bit. The images, however, are still mostly shown in green, black and white, with the colors out of reach for night vision users. Now, the researchers of theUniversity of California Irvine have developed a solution that could pave the way for color night vision technologies.
Machine learning, always him
in study just published, the researchers illustrate the algorithm they developed. An artificial intelligence model that “learns” to derive useful elements from the data of an infrared image to transform it into a color image.
The technological breakthrough was possible thanks to the use of a monochromatic camera sensitive to both visible and near infrared light. The camera was used to capture printed images of human faces under red, green and blue wavelengths as well as infrared wavelengths.
Thanks to these "data pairs" obtained, a neural network was able to begin to "learn" the possible association of infrared data with those of the visible spectrum.
Result? The system (similar to a GAN, here I explain what it is) successfully recreated a color image from black and white only.
Possible applications of color night vision
You probably don't need a crystal ball to imagine them. Unfortunately, the first, immediate applications are those in the military field (night vision systems are crucial and often used in training or combat theaters). However, other possibilities open up for all applications that require clear observation even in the dark: that for research purposes concerning animals, for example.
Further on, such a system (thanks to the speed of calculation and the power of future computers) will allow us to see in real time at night, or underwater, as if we were observing a scene in the sunlight.
