Astronomical Image Processing
Astronomical Image Processing is a specialized field that enables the creation and refinement of images of celestial objects, which are often challenging to capture due to their vast distances and inherent complexities. Space telescopes, unlike traditional cameras, are designed to collect data across various wavelengths of electromagnetic radiation, including infrared and ultraviolet, necessitating advanced processing techniques to visualize these observations. The process typically involves the use of charge-coupled devices (CCDs) to gather raw data, which is then transformed into images through specialized software that can enhance visibility and clarity.
These images are constructed from a grid of pixels, with each pixel representing specific color values based on the chosen color model. Researchers frequently employ algorithms, such as the Drizzle algorithm, to stack multiple images, providing a more comprehensive view of an object that might be too large for a single photograph. The resulting images not only help in scientific studies but also contribute to popular media representations of space phenomena. Importantly, much of the raw data from major telescopes, like the Hubble Space Telescope, is publicly available, allowing amateur astronomers and enthusiasts to partake in image processing and contribute to astronomical research. This collaborative effort has led to significant discoveries about the universe, including insights into the age of the universe, the existence of dark matter, and the dynamics of celestial events.
Astronomical Image Processing
FIELDS OF STUDY: Astronomy; Space Technology
ABSTRACT: The instruments used to gather space data are designed to gather scientific information and not necessarily to produce high-quality photographic images. Astronomical image processing allows scientists and amateur enthusiasts alike to produce high-quality images of distant stellar objects. Astronomical image processing uses specialized equipment and software to filter and combine multiple images from space telescopes. These images often provide a dramatic look at stellar objects in distant parts of the universe.
Refining Raw Data
It can be difficult to produce images of stellar objects. First, space telescopes are not designed to produce the kind of images taken by a traditional camera. Second, stellar objects are far from Earth and are often too large to fit in a single image. In addition, some space objects, such as new stars, are hidden by clouds of dust and gas. Astronomical image processing allows researchers to overcome these problems by creating composite images of stellar objects to use in scientific study. This process is often used to create the images of galaxies, planets, and other space objects that appear in popular media.
To detect and study celestial objects, researchers use instruments that detect electromagnetic radiation outside the visible light spectrum, such as infrared, ultraviolet, or x-rays. The images produced by these instruments are often colored differently from the actual objects themselves. Researchers use filters, software, and other photographic techniques to refine such images. The process can involve combining multiple images of the same object to create a single, more complete picture.
How Astronomical Images Are Made
All digital images are formed from a matrix, or grid, of pixels. The placement and color of each pixel in relation to those alongside it create the image. Even grayscale images are made of pixels. Each pixel has an assigned value that determines its color or shade. Depending on the color model being used, the pixels might represent shades in the red, green, and blue (RGB) spectrum, or they might represent shades in the cyan, magenta, yellow, and black (CMYK) spectrum. The stacking of these colors creates all the visible colors in an image.
While some telescopes use color filters to collect images, most produce grayscale images. These images are taken with a charge-coupled device (CCD). CCDs are more sensitive to photons than standard photography equipment and therefore yield much more detailed images. They capture the data digitally, making it easier to access, transmit, and share.
An image processor can highlight areas of interest to researchers or minimize items, such as dust and gas clouds, that obstruct the image. This is done using specialized software designed for the purpose. A processor working with raw data from a CCD would first load the data into a program to produce the desired image type. The type of image varies depending on the image’s intended use. A processor who wants to release a photograph of a newly discovered galaxy to the media will produce a dramatic, colorful image. On the other hand, a researcher who wants to determine the number and types of stars in an area will create an image that makes counting and categorizing the stars easier, without much care for its attractiveness.
The processor might choose to stack the image using the Drizzle algorithm. An algorithm is a step-by-step problem-solving process. Drizzling stacks multiple images of the same object, allowing a fuller view than could be captured in any one image. This algorithm could be used to fill in areas that are blocked by cosmic rays, for example. It could also be used to render a complete image of a large object, such as a galaxy, that would impossible to capture completely in a single image.
If the final color of the image is important, the processor will apply filters that assign color values to the grayscale pixels. In some cases, colors other than the object’s actual colors are used. For instance, if a dust cloud surrounding a new star is nearly the same color as the star, it might be shown in a different color. Researchers call these representative color images.
Uses for Astronomical Images
The photos made from the data collected by giant telescopes have given researchers great insight into the universe. For example, by studying a particular type of star called a Cepheid variable using data and images from the Hubble Space Telescope (HST), researchers from the US National Aeronautics and Space Administration (NASA) were able to determine that the universe is about 13.7 billion years old, give or take 200 million years.
Other discoveries made with Hubble images include proof that dark matter exists, proof that black holes are probably the forces that create galaxies, and proof that the universe has been expanding since its creation. In early 2015, images from the Hubble captured the rarely seen phenomenon of an exploding star and provided a glimpse of three of Jupiter’s moons against the planet’s face. Its other discoveries since then include a moon orbiting Makemake, the second brightest icy dwarf planet in the Kuiper Belt; the farthest star yet discovered, nicknamed Icarus; 'Oumuamua, the first known interstellar object to pass through the solar system; and water vapor in the atmosphere of exoplanet K2-18b. In 2020, Hubble tracked Comet Borisov, the second known interstellar object.
NASA’s Wide-Field Infrared Survey Explorer (WISE) telescope focuses on infrared data. Among other tasks, it has provided information on the location of a number of failed stars, known as brown dwarves. In 2013, NASA initiated the project NEOWISE that used WISE to study near-Earth objects (NEOs). It discovered the first Earth Trojan asteroid, an asteroid that shares the orbit with a planet. In 2020 astronomers identified one of the brightest comets yet discovered and named it for the program, Comet NEOWISE. In 2021, NASA approved the development of a space telescope NEO Surveyor with heat-sensing cameras to find NEOs that can pose a threat to Earth.
In 2021, Hubble’s observations were suspended due to a degrading memory module, which took a month to repair. NASA planned to launch the James Webb Space Telescope (JWST or popularly known as the Webb) as Hubble’s successor. It can observe deeper (up to 1 million miles) into the infrared regions of the electromagnetic spectrum than Hubble.
Not for Professionals Only
Access to first-hand scientific information is often limited to researchers working for governments, agencies, or universities. However, the raw data gathered from the giant space telescopes is available to anyone. The image archive for the Hubble telescope has more than twenty years’ worth of data. The government agencies responsible for this data have made it available to the public.
Numerous volunteer image processors, including academics, amateur photographers, and astronomy enthusiasts, have produced images of star-forming regions in the Large Magellanic Cloud, the center of the Messier 77 (M77) galaxy, and a newly formed star in a spray of gas. In 2009, astronauts renewed the array on the Hubble to keep gathering data for new deep-space discoveries by scientists and enthusiasts alike.
PRINCIPAL TERMS
- grayscale: a photographic image produced in shades of gray rather than in color, commonly referred to as a black-and-white image.
- matrix: the arrangement or grid of pixels that make up a digital image.
- pixel: a small square of a single color that is the smallest discrete component of a digital image.
Bibliography
"Breakthroughs in Cosmology: Taking the Universe’s Baby Pictures." HubbleSite. NASA, n.d. Web. 7 Apr. 2015.
Cruz, Lia De La. "Hubble Space Telescope Returns to Normal Operations." EarthSky Communications, 18 July 2021, earthsky.org/space/hubble-in-safe-mode-june-july-2021. Accessed 26 July 2021.
Ferguson, Harry, and Andy Fruchter. "Drizzle." Space Telescope Science Institute. STScI, 1997. Web. 7 Apr. 2015.
Hall, Geoffrey. "Astronomical Image Processing A1." Workspace: Physics Undergraduate Laboratories. Imperial Coll. London, 6 Mar. 2015. Web. 7 Apr. 2015.
"Hubble Image Processors: Raiders of the Hubble Archive." HubbleSite. NASA, n.d. Web. 7 Apr. 2015.
Netting, Ruth. "Infrared Waves." Mission:Science. NASA, 13 Aug. 2014. Web. 7 Apr. 2015
Peterson, Kit A. "Introduction to Basic Measures of a Digital Image for Pictorial Collections." Library of Congress Prints & Photographs Division. LOC, June 2005. Web. 7 Apr. 2015.
"A Short Introduction to Astronomical Image Processing." Hubble Space Telescope. European Space Agency, n.d. Web. 7 Apr. 2015.
Stolte, Daniel. "UArizona to Lead Mission to Discover Potentially Dangerous Asteroids." University of Arizona, 11 June 2021, news.arizona.edu/story/uarizona-lead-mission-discover-potentially-dangerous-asteroids. Accessed 26 July 2021.
Zuckerman, Catherine. "Hubble Pictures: Top Five Hidden Treasures." National Geographic. Natl. Geographic Soc., 4 Sept. 2012. Web. 7 Apr. 2015.