Quality Control

Numerous factors play an important role in the final outcome of a digitization project. Original condition of materials, quality and maintenance of equipment, staff training and external lighting are some factors that can influence the quality of images.

A quality control program should be conducted throughout all phases of the digital conversion process. Inspection of final digital image files should be incorporated into your project workflow. Typically, master image files are inspected online for a variety of defects. Depending on your project, you may want to inspect 100 percent of the master images or 10 percent of the files randomly.  We do recommend that quality control procedures be implemented and documented and that you have clearly defined the specific defects that you find unacceptable in an image. Images should be inspected while viewing at a 1:1 pixel ratio or at 100 percent magnification or higher.  Quality is evaluated both subjectively, by project staff (scanner operator, image editors, etc.) through visual inspection, and objectively, in the imaging software (by using targets, histograms, etc.). 
 
Tonal Dynamic Range
As noted earlier, one of the most significant factors affecting image quality is the Tonal Dynamic Range ― the color space an image occupies between pure black (0) and pure white (255). Reviewing histograms at the time of capture can ensure that all of the image’s information is being recorded. When the white and black points are not set on true white and black during the set up of the capture, clipping and spiking can occur.

White & Black Points
Optimum placement of whites and blacks is best observed through the histogram, although the image itself will be examined without the histogram on the screen. It is important to look at the number value assigned to the brightest highlight and the darkest shadow. Highlights should not read a number value higher than 247 and shadows should not be less than 7 or 8. If these numbers are exceeded, the scan must be redone. This is particularly vital if the original image has a short dynamic range. The white and black points must not be set on 0 and 255, as this will stretch the dynamic range of the image, creating gaps in the histograms, and thus unusable scans. These adjustments need to be made at the time of scanning since adjusting images after the fact in image editing software introduces interpolation of the dynamic range (guessing what the points are in the image) and frequently results in gaps in the histogram rather than continuous
curves.

Clipping & Spiking
Clipping and spiking result when the white and black points are not set on true white and black during the set up of the scan. If white and black are improperly set, everything above or below those points is clipped, or registers as the same tone. Spiking on the ends of the histogram usually indicates clipping. This problem also shows up in the image itself as blockage and pixelization in the shadows and blowouts in the highlights. Acceptable spikes can occur if the edge of the original negative has lost emulsion, for example, or the sky holds no detail and is one tone in the original. Such instances, however, are rare.

Black and White images
(Left) Detail in the image on the left has been lost due to improperly adjusted white and black points. The histogram shows the “clipping and spiking” associated with incorrect points. The image on the right shows properly adjusted white and black points with no clipping or spiking in the histogram.

 (Left) Rocky coastline on Forrester Island, 1920; courtesy Denver Museum of Nature and Science. (Right) Downtown Colorado Springs, 1964; courtesy Pikes Peak Library System.

Color Management
Color management can be one of the most challenging aspects of the digitization workflow. Each piece of hardware in the path from source to digital file can introduce biases of color and tone. The goal of color management procedures is to accurately and predictably compensate for each of these biases across the entire workflow from scanner to print output or monitor display.

Applying the practices outlined below will allow you to fine tune the color captured in the image. This assumes, however, that prior to capture, accurate lighting is in place, capture equipment and display devices have been regularly calibrated and a proper light source is available to accurately view analog materials. Take time to evaluate and test all your equipment and accessories before image capture so that you can minimize, if not eliminate, the need for extensive post-capture color management.

Projects not undertaking color management should be aware that equipment will introduce color biases into any digitized materials. Attempting to make digitized materials “look good” on uncalibrated equipment may introduce these biases into the master images. Projects without a color management system should use available tools to perform basic monitor calibrations:

Targets and Color Bars
Targets and color bars are used to measure system resolution, tonal range and color fidelity. Including targets in a digitization workflow allows color management systems to create profiles for each device or for later adjustment in projects not implementing color management during image capture. Targets are a way of predicting image quality and help ensure that the imaging system you are using is producing the best quality image it can and is operating at a consistent level of quality over time. Targets for prints and transparencies exist, and targets appropriate for the materials being scanned should be used (paper, film, transparency, etc.). Targets usually contain patches of color, black and white or shades of gray for verifying tone reproduction. Resolution targets allow projects to measure the level of detail a particular piece of equipment can capture. Resolution targets can be helpful in evaluating equipment before purchase or assessing the quality of output from a vendor.

[Insert MacBethTarget shot here]

As equipment biases can shift over time, best practice is to include targets on a regular basis throughout the course of the project. Some digitization projects also scan a color bar along with the original, to be included in the final digital image, to aid users in verifying accuracy in color reproduction. See Appendix E for a tutorial on how to use targets and color bars.

Color Targets

Visual Inspection
Things to look for during archival master visual inspection may include: (Note: If these attributes, with the exception of file name, are met, then you do not need to re-capture the item.)

If levels and curves are adjusted in the service master, then you should check the histogram again.

The service master will be checked for:

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