A New Image File Format Efficiently Stores Invisible Light Data

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 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, 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 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 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.'

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