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Robert D Feinman

Scanning Black and White Negatives

Scanners have trouble scanning black and white negatives.
The negatives have a small density range, typically less than 2.0. Scanners attempt to spread this range over the 256 levels, but are really set up to handle the 3.0 to 4.0 density range of transparencies.
The result is the scan has poor separation in the shadows and poor gradation. Here is a an 8 bit scan of a negative using the automatic settings
.

[Note: Newer scanners and improved software have been released since this tip was written. If you have one of these products try turning off all clipping of the shadows and highlights and using 16 bit scanning, before trying this technique. The scan will look low in contrast after scanning, but can be improved using the curve techniques shown below.]

8 bit scan
8 Bit Scan

Here is the histogram for this scan.
Notice how most of the values are bunched up at the dark end. There is a small tail at high values caused by the white spot on the top of the building.

8bit histogram
8 Bit Histogram

We attempt to improve the gradations in the picture by applying a curve. We used the automatic feature in Photoshop. Notice how little of the range is used by the curve tool in an attempt to spread out the values.

8bit curve
8 Bit Curve

Here is the resulting image.The contrast is better, but the foreground is still too dark.

8bit curve
After Automatic Curve

We try to remedy this by applying a second curve to open up the shadows. Here is the curve. The steep rise in the shadows is supposed to separate the tones. We have to compensate by flattening the high tones.

8bit curve
Shadow Detail Curve

Here is the resulting image. There are still no good details in the shadows, although the clouds and the building are better.

after 8 bit curve
After Shadow Detail Curve

All this stretching has taken a toll on the tonal range. Look at the resulting histogram now. The image is severely posterized, with very few gradations and big gaps between steps. Ugly!
Let's try again...

final histogram
Final 8 bit Histogram

This time we scan the negative as a transparency. The scanner now spreads the values better. In addition we use the hi bit mode of the scanner to give us more tones to deal with. This scanner uses 12 bits in high bit mode. We also scanned the image as a color image even though it is black and white. That way we use all the sensors in the scanner. We can average the red, blue and green values together in Photoshop. The imported image is a black and white negative.

High bit scan
Hi Bit Scan

Here is the histogram of the original image. Compare this with the 8 bit histogram. See how the values are spread over a greater range of tones.

Hi bit Histogram
Hi Bit Histogram

Next we invert the image. This turns black to white, etc.
Notice that the image looks better already. There is detail in the foreground!

inverted iamge
Inverted Image

Now we apply a curve to this image. We darken the shadows a bit and brighten the highlights. This curve is much less radical that the first curve in 8 bit mode.

Hi bit Histogram
Hi Bit Curve

Here is the image after this curve has been applied. The sky is a little brighter and the base of the flagpole is a little darker.

After first curve
After Curve

Since we have more tonal values to deal with we can try other treatments. In this case we brighten the dark tones more to give a brighter foreground.

Hi bit Histogram
Hi Bit Curve

Here is the image after this second curve has been applied. The foreground is brighter than in the other treatment. There are enough values so that we can now use artistic judgments to produce the desired image.

After second curve
After Second Curve

Here is histogram of the final image. Quite a change from the 8 bit version! There is a good range of values and no gaps. Note this histogram is reversed from the first one since we also inverted the tones when we imported the image.

With a little bit of adjustment to the color balance we get this image.

Hi bit final histogram
Hi Bit Final Histogram

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© 2001 Robert D Feinman, revised 2008