The arguments for and against using JPEG 2000 lossy files for long-term preservation are largely centred around two issues: 1) that the original capture image is the true representation of the physical item, and therefore all the information captured at digitisation should be preserved; and 2) that lossy compression (as opposed to lossless compression) will permanently discard some of this important information from the digital image. Both of these statements can be challenged, and the Buckley/Tanner report went some way to doing this.
The perceived fidelity of the original captured image is the root of the attachment to lossless image formats. As cameras have improved, so has the volume of information captured in the RAW files. This volume of information has of course improved the visual quality and accuracy of the images, but this comes at the cost of inflated file sizes. A high-end dSLR camera will produce RAW files of around 12Mb. A RAW file produced by a medium-format camera may be 50Mb or higher. When a RAW file is converted to a TIFF, file sizes can increase dramatically depending on the bit-depth chosen due to interpolating RGB values for each pixel captured in the RAW file. As RAW files can only be rendered (read) by the proprietary software of the camera manufacturer (which may include plugins for 3rd party applications like Photoshop), they cannot be used for access purposes and, being proprietary, are not a good preservation format. They must be converted to a format suited to long term management, and this has usually been TIFF. When a RAW file is converted to a TIFF, file sizes can increase dramatically depending on the bit-depth chosen due to interpolating RGB values for each pixel captured in the RAW file. This bloats the storage requirements by 2 to 4 times.
However, image capture and subsequent storage of large images, is expensive, and we don’t want to have to redigitise objects ever if we can get away with it – particularly for large scale projects. So, how much of a compromise is lossy compression, and is it really worth it? The question is: what information are we actually capturing in our digital images? Do we we need all that information? Is any of it redundant?
First – the visual fidelity issue. Fidelity to what information? The visual appearance of a physical item as defined by one person in a particular light? The visual appearance as perceived through a specific type of lens? All the pixels and colour information contained in the image as captured under particular conditions? No two images taken through the same camera even seconds apart will look the same due to distortions caused by the equipment, and, possibly, noise levels. What makes any particular pixel the original representation, or the most accurate, or indeed at all important?
Lossy compression will permanently discard data. What is necessary is to determine – for any given object, set of objects, or purpose – what information is actually useful and necessary to retain. We already balance these decisions at the capture stage. Choosing to use a small-format camera immediately limits the amount of information that can be detected by the camera sensor. Choosing one lens over another introduces a slightly different distortion. Compression also represents a choice between what you can capture and what you actually need. One may not need all the information that has been captured; some of it may be redundant. A lot of it may be redundant. And the point of JPEG 2000 is that it is very good at removing redundant information.
At the Wellcome Library, the aim of our large-scale digitisation projects is to provide access. We do not want to redigitise in the future, but we do not see the digital manifestations as the “preservation” objects. The physical item is the preservation copy, whether that is a book, a unique oil painting, or a copy of a letter to Francis Crick. For us, the important information captured in a digital manifestation are the human-visible properties. Images should be clear and in-focus, details visible on the original should be visible in the image (so it must be large enough to see quite small details), colour should be as close to the original as possible in daylight conditions and consistent, and there should be no visible digital artefacts at 100%. This is the standard for an image as captured.
We are striking a balance. Can we compress this image and retain all these important qualities? Yes. Do we need to retain information that doesn’t have any relevance to these qualities? No. Lossy compression works for us. Using these qualities as a basis, we set out a testing strategy to determine how much compression our images could withstand.
To be continued…