Lead Image Processor for the James Webb Space Telescope, Joe DePasquale explains how you can apply the processes he uses to create JWST’s stunning images to enhance your own astrophotos
On a recent trip to London, my family and I had a chance to visit the Royal Observatory in Greenwich. I’ve always been fascinated by the challenges faced by sea-faring explorers of the 18th century, who needed accurate methods to track a ship’s location on the ocean but hadn’t cracked the problem until John Harrison perfected his marine chronometer in 1759 (which is on display in the observatory). We can draw direct parallels between space-based observatories – seeking answers to the big questions about our place in the Universe – and those intrepid oceanic explorers who set sail with the goal of exploring the unknown reaches of the world. The James Webb Space Telescope, with its huge sun shield deployed like the sail of a cosmic ship, is the latest of our great explorers, orbiting an imaginary point a million miles away as its giant golden mirror array captures light that has been streaming across the Universe for billions of years.
How lucky are we to live in a time when we can work with this ancient light? And not only Webb – even a decent backyard telescope is capable of providing views of the cosmos that would have blown the wig off of any Astronomer Royal in Greenwich! Many of the techniques I use in processing Webb data are easily transferrable to data obtained from backyard telescopes. Let’s journey through the process of working with calibrated data from any telescope, transforming it into colourful views of the cosmos.
Data stretching
What exactly do we mean by ‘stretching’, and why do we need to do it? Stretching here refers to the values of the individual pixels that make up the image. Modern charge-coupled devices (CCDs) are so sensitive to light that the images they produce have an enormous dynamic range, far beyond what can be seen with the eye. In a 16-bit monochromatic image, each pixel can be one of 65,536 different shades of grey. This specific number is directly related to the digital nature of the data. A bit can be one of two values, 0 or 1. In a 16-bit image, each pixel holds a value defined by a sequence of 16 bits where 0000000000000000 is pure black and 1111111111111111 is pure white. The total amount
