We’ve all seen beautiful images of space, including vivid swirls and bright stars floating in a black abyss. Since the iPhone takes color photos so quickly, you might think that even sophisticated space telescopes would automatically produce large amounts of color photos.
However, all digital cameras, from cell phones to the James Webb Space Telescope, can’t actually see in color. Digital cameras record images as a collection of ones and zeros, counting the amount of light that hits the sensor. Each pixel has a colored filter (either red, green, or blue) that allows only certain wavelengths of light to pass through. A filter is a specific pattern (usually bayer pattern), which allows the camera’s computing hardware to combine the captured data into a full-color image. Some digital cameras can distribute their color filters across three separate sensors and similarly combine the data from them to create a full-color image. However, since the telescope camera requires him to take images using one filter at a time, these images must later be combined by an expert to create a composite image.
Processing scientific data into beautiful color images is actually a full-time job.
Our smartphones combine layers incredibly quickly, but telescopes are complex scientific giants that require a little more effort to achieve the great results we know. Moreover, when we look at the universe, astronomers use wavelengths of light that are invisible to our eyes (such as infrared and X-rays), so they must also be represented in the colors of the rainbow. Many decisions need to be made about how to color space images, which raises the question of who is creating these images and how.
As impressive as the results we’ve seen from JWST, processing scientific data into beautiful color images is actually a full-time job. Scientific visualization expert at the Space Telescope Science Institute in Baltimore It superimposes images and stitches together observations from different instruments on the telescope. It also removes artifacts, objects in the image that are not actually real, but instead are just a result of the telescope’s equipment and the way it processes digital data. These could be streaks from stray cosmic rays, oversaturation of the brightest stars, or noise from the detector itself.
black and white in color
These professionals need to balance the dark and light values in the image before thinking about color. Scientific cameras aim to record a wide range of brightness beyond what our eyes can perceive. This means that the raw image from a telescope often appears very dark to our eyes, and we need to make the image brighter in order to see anything.
Once you have a black and white image with some detail visible, start adding color. “Different telescopes have filters made to respond only to specific wavelengths of light, and the colorful cosmic images we see are a combination of separate exposures taken with these different filters. ”, similar to the previous explanation regarding cell phone cameras. Katia Gozman, astronomer at the University of Michigan. “Each filter can be assigned to a separate color channel (the primary colors of visible light: red, green, and blue). When stacked together, you get the great textbook color images you’re used to seeing in the media,” she adds. I did.
Now it becomes a bit of an art, choosing colors based on what looks best, not just scientific accuracy. JWST and Hubble typically use blue for the shortest wavelengths, green for wavelengths in between, and red for the longest wavelengths.
Of course, the final result also depends on what kind of data the image professional needs to work with in the first place. The researchers highlight the fact that two of Webb’s thermal imaging cameras, NIRCam and MIRI, observe different wavelengths (near-infrared and mid-infrared, respectively) and therefore different physical structures. We often choose different colors for this purpose. For example, in the Cassiopeia A-type supernova remnant, JWST observations show that something It emits a specific wavelength of light and is colored green in MIRI images, resulting in it being known as the “green monster.” Without this visualization, astronomers might not have noticed such interesting features that provide insight into how giant stars die. And after some research they discovered the following: The Green Monster is a field of debris disturbed by a huge explosion caused by a supernova explosion.
From the invisible to the visible
Image professionals generally try to keep things as close to reality as possible. For example, if a telescope is observing in visible light, the wavelengths can be mapped directly to the colors we are accustomed to seeing. But for the parts of the spectrum that are invisible to our eyes, we have to choose which visible colors to use. Now it becomes a bit of an art, choosing colors based on what looks best, not just scientific accuracy. For JWST and Hubble, typically The routine is to use blue for the shortest wavelength, green for the wavelengths in between, and red for the longest wavelength.. If you have three or more different filters to choose from (as is often the case with JWST, especially when using multiple high-tech equipment), other wavelengths in between may include violet, blue-green, and orange. . They are red, green, and blue.
However, color images are not just pretty images; they are actually very useful for science. The human brain is good at recognizing color patterns, such as parsing maps with color-coded subway lines and recognizing that red lights mean stop and green lights go. Mark Popinchalk, astronomer at the American Museum of Natural History. “These are everyday examples where social information is quickly displayed and processed in color. Scientists want to use the same tools,” he added. “But it’s not social information, it’s scientific information. If X-rays are red and ultraviolet light is blue, we can very quickly interpret high-energy light that is beyond human ability. ” The result is a visual representation of much more data than can be processed by the naked eye or black and white alone.
For example, Gosman describes how images helped him recognize “where different physical processes are happening inside objects.” For example, you can see where star formation is occurring in a galaxy or where different elements are located around a nebula. Color images using light beyond the visible spectrum even revealed the dark matter surrounding the galaxy. bullet cluster.
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Some particularly interesting recent examples of image color schemes include: For Neptune. The dark blue photos of the icy world taken by the Voyager mission do not actually reflect its true color, but rather the paleness of Uranus, as if we were seeing it with our own eyes. It resembles a face. “Back in the ’80s, astronomers actually stretched and modified images of Neptune to increase the contrast in its faint areas and give it a deep blue hue, making it look very different compared to Uranus. ” Gosman explains. “Astronomers knew this, but the general public didn’t. This is a good example of how reprocessing the same data in different ways can yield very different representations.”
Image analysis is, and always has been, a big part of astronomy, finding ways to see the universe beyond the limits of the very limited human eye. JWST data is publicly available from NASA and can also be run. Astrophotography challenge that anyone can participate in. Now, when you look at beautiful images of the universe, you might think that it is a wonderful combination of science and art.
