THE EFFECTS OF USING NIKON SCAN'S MULTISAMPLING

Multisampling is a feature that is designed to reduce noise by averaging the pixel values from multiple samples. The theory is that since noise is inherently random, noise will cancel itself out when the values are averaged over multiple readings. In this section, we will examine a slide to study the effects of using multisampling on images that aren't manipulated as well as on images that are heavily manipulated.

The methodology used involves scanning the same slide twice in 14 bit mode and Adobe RGB color space on a Nikon Super Coolscan 4000. One scan is made without multisampling and the other is made with multisampling set to 16X. These images are then cropped at "actual pixels" size, converted to sRGB color space, converted to 24 bit (8 bits per channel) images, and saved out as high quality (Q = 90) jpgs in Photoshop to make them viewable on the web. The 2 original scans then have their histograms adjusted in Photoshop (in 16 bit mode) to study the effects of Multisampling on images that are heavily manipulated. Here, their white points are set to 200 and their gammas are set to 1.4. The exporting process is repeated to make these images viewable on the web. This system is not perfect due to the compression of the images and other factors but I believe it accurately shows the differences (or lack thereof) between using Multisampling and not using Multisampling.

With the older Nikon Scanners, using multiscan yielded obvious benefits because the CCDs of these older scanners were fairly noisy. With the Coolscan 4000/8000 scanners however, it is much more difficult to tell the difference because the noise levels are already so low. From viewing the unedited images tested here, there was little to no difference between the image scanned using multisampling and the image scanned without multisampling. When the images have their levels adjusted to brighten the image however, the differences are more prominent because the noise is gained along with the rest of the image.

CONCLUSION: Since using this feature greatly increases scan times, it is recommended that multisampling not be used for images that will not be heavily edited if you are using the Super Coolscan 4000 or 8000. If you are going to be applying heavy levels adjustments to the image though, Multisampling will be useful in reducing the noise in the final image.