A New Image File Format Efficiently Stores Invisible Light Data (arstechnica.com)
(Friday March 28, 2025 @11:30PM (BeauHD)
from the world-beyond-RGB dept.)
- Reference: 0176851707
- News link: https://science.slashdot.org/story/25/03/28/232215/a-new-image-file-format-efficiently-stores-invisible-light-data
- Source link: https://arstechnica.com/science/2025/03/scientists-are-storing-light-we-cannot-see-in-formats-meant-for-human-eyes/
An anonymous reader quotes a report from Ars Technica:
> Imagine working with special cameras that capture light your eyes can't even see -- ultraviolet rays that cause sunburn, infrared heat signatures that reveal hidden writing, or specific wavelengths that plants use for photosynthesis. Or perhaps using a special camera designed to distinguish the subtle visible differences that make paint colors appear just right under specific lighting. Scientists and engineers do this every day, and they're drowning in the resulting data. A new compression format called Spectral [1]JPEG XL might finally solve this growing problem in scientific visualization and computer graphics. Researchers Alban Fichet and Christoph Peters of Intel Corporation detailed the format in a recent paper published in the Journal of Computer Graphics Techniques (JCGT). It tackles a serious bottleneck for industries working with these specialized images. These spectral files can contain 30, 100, or more data points per pixel, causing file sizes to balloon into multi-gigabyte territory -- making them unwieldy to store and analyze.
>
> [...] The current standard format for storing this kind of data, [2]OpenEXR , wasn't designed with these massive spectral requirements in mind. Even with built-in lossless compression methods like ZIP, the files remain unwieldy for practical work as these methods struggle with the large number of spectral channels. Spectral JPEG XL utilizes a technique used with human-visible images, a math trick called a [3]discrete cosine transform (DCT), to make these massive files smaller. Instead of storing the exact light intensity at every single wavelength (which creates huge files), it transforms this information into a different form. [...]
>
> According to the researchers, the massive file sizes of spectral images have reportedly been a real barrier to adoption in industries that would benefit from their accuracy. Smaller files mean faster transfer times, reduced storage costs, and the ability to work with these images more interactively without specialized hardware. The results reported by the researchers seem impressive -- with their technique, spectral image files [4]shrink by 10 to 60 times compared to standard OpenEXR lossless compression , bringing them down to sizes comparable to regular high-quality photos. They also preserve key OpenEXR features like metadata and high dynamic range support.
The report notes that broader adoption "hinges on the continued development and refinement of the software tools that handle JPEG XL encoding and decoding."
Some scientific applications may also see JPEG XL's lossy approach as a drawback. "Some researchers working with spectral data might readily accept the trade-off for the practical benefits of smaller files and faster processing," reports Ars. "Others handling particularly sensitive measurements might need to seek alternative methods of storage."
[1] https://en.wikipedia.org/wiki/JPEG_XL
[2] https://openexr.com/en/latest/
[3] https://en.wikipedia.org/wiki/Discrete_cosine_transform
[4] https://arstechnica.com/science/2025/03/scientists-are-storing-light-we-cannot-see-in-formats-meant-for-human-eyes/
> Imagine working with special cameras that capture light your eyes can't even see -- ultraviolet rays that cause sunburn, infrared heat signatures that reveal hidden writing, or specific wavelengths that plants use for photosynthesis. Or perhaps using a special camera designed to distinguish the subtle visible differences that make paint colors appear just right under specific lighting. Scientists and engineers do this every day, and they're drowning in the resulting data. A new compression format called Spectral [1]JPEG XL might finally solve this growing problem in scientific visualization and computer graphics. Researchers Alban Fichet and Christoph Peters of Intel Corporation detailed the format in a recent paper published in the Journal of Computer Graphics Techniques (JCGT). It tackles a serious bottleneck for industries working with these specialized images. These spectral files can contain 30, 100, or more data points per pixel, causing file sizes to balloon into multi-gigabyte territory -- making them unwieldy to store and analyze.
>
> [...] The current standard format for storing this kind of data, [2]OpenEXR , wasn't designed with these massive spectral requirements in mind. Even with built-in lossless compression methods like ZIP, the files remain unwieldy for practical work as these methods struggle with the large number of spectral channels. Spectral JPEG XL utilizes a technique used with human-visible images, a math trick called a [3]discrete cosine transform (DCT), to make these massive files smaller. Instead of storing the exact light intensity at every single wavelength (which creates huge files), it transforms this information into a different form. [...]
>
> According to the researchers, the massive file sizes of spectral images have reportedly been a real barrier to adoption in industries that would benefit from their accuracy. Smaller files mean faster transfer times, reduced storage costs, and the ability to work with these images more interactively without specialized hardware. The results reported by the researchers seem impressive -- with their technique, spectral image files [4]shrink by 10 to 60 times compared to standard OpenEXR lossless compression , bringing them down to sizes comparable to regular high-quality photos. They also preserve key OpenEXR features like metadata and high dynamic range support.
The report notes that broader adoption "hinges on the continued development and refinement of the software tools that handle JPEG XL encoding and decoding."
Some scientific applications may also see JPEG XL's lossy approach as a drawback. "Some researchers working with spectral data might readily accept the trade-off for the practical benefits of smaller files and faster processing," reports Ars. "Others handling particularly sensitive measurements might need to seek alternative methods of storage."
[1] https://en.wikipedia.org/wiki/JPEG_XL
[2] https://openexr.com/en/latest/
[3] https://en.wikipedia.org/wiki/Discrete_cosine_transform
[4] https://arstechnica.com/science/2025/03/scientists-are-storing-light-we-cannot-see-in-formats-meant-for-human-eyes/
Ye olde? (Score:2)
by pipatron ( 966506 )
That's weird, why wasn't this already standard practice?
The idea of collecting the energy from multiple layers like DSP 101, I first read about it in graphics literature from the early nineties when I started, and multi-spectral images in astronomy is the standard example of where this is useful.
Of course JPEG and many other related formats already do this with the RGB layers but with a hardcoded transform designed as a decent compromise between image perception and being easy to calculate.
Re: Ye olde? (Score:1)
by RightwingNutjob ( 1302813 )
It's not standard practice because for people who collect spectra, the interesting bits are precisely what's lost by compression.
Compression by DCT saves space by eliminating high-frequency parts of the data. The high-frequency parts of a spectrum correspond precisely to absorption or emission lines that are often (but not always) the thing you want to measure with a hyperspectral imager to begin with.
At first I thought... (Score:3)
At first I thought, well duh, just use EXR since it can accommodate an arbitrary number of layers. Though they're usually used for matte layers, you could assign a layer per range of wavelength, that sort of thing.
What the article seems to be getting at however, I think, is instead of just doing compression in the X & Y direction, also do compression in, I guess, the Z direction? i.e. across the spectrum of interest?
Re: (Score:3)
Yes, they seem to be compressing in the direction often written as lambda (wavelength). EXR could store the individual wavelengths as MainLayer.450nm, MainLayer.460nm etc instead of MainLayer.R, .G and .B. But it would compress each layer individually, rather than exploit the coherence across X,Y,Lambda and potentially Time