Comparing B&W conversion methods

Although I have already blogged about it, converting images to Black & White is a bit like the recipe of the Swiss Fondue: everyone has his own touch to it and claims his way to be “the genuine one”. So I decided to revisit the subject (B&W converting that is, not the fondue) and try several conversion methods and see what results are offered. The methods are:

1. Simple desaturation with RawStudio
2. Use a channel mixer
3. Use the Luminance curve
4. Use the special Jpeg2BW tool by Thomas Baruchel

The picture I will use as an example is that one, taken on the side of the Lake of Lucerne.

By the way, speaking of Fondue and Lake of Lucerne is timely, since August 1st is the Swiss National Day 🙂

Foreword

My goal is to see how much difference there is between several conversion methods in one real life case.

Practically, I tweaked my file in RawStudio to create the base image (above). I then used this same image to generate the different B&W versions. So what we see here is really the effect of different conversion methods.

And instead of just presenting each result on the way, I have decided to do a little challenge (à la Meetthegimp.org): the b/w versions are available at the bottom of this post without mention of the method used. I would be interested to read your comments on how you like the different outputs and why.

Desaturation & Curves in RawStudio

I said myself that you shouldn’t do that… but I do it more often than not. It is so easy – just put the saturation to 0 and you can get a decent B&W picture in no time; the curve tool is so powerful and RAW offers such a latitude of treatment.

Will that make a good final output, however?

Channel Mixer

This is the “proper way” to do B&W conversion. You basically mix the Red Green and Blue components of the image – usually with alot of green, a bit of red and almost no blue. Although red is the most “spectacular” channel, green has less noise (since there are twice more green photosites than blue and red) so using a good chunk of it is a safe bet.

This is the method I described previously.

Luminance Channel

This is another technique presented as offering very good results. Luminance offers an excellent basis for a B&W image; just decompose your image to LSV and use the L channel – unfortunately, this had to be done in 8 bits since I didn’t find a way to do it in Cinepaint.

Jpeg2BW by Thomas Baruchel

In a comment, Thomas Baruchel said that he had developed his own B&W conversion routine that he as put as a command line tool on sourceforge – it basically takes a JPG file as income and spits out a B&W “optimized” image. You can read the details of his conversion method in French on his blog (part 1, part 2) or in English with the Jpeg2BW program itself.

Jpeg2BW is straightforward to compile, just use Guile 1.8 (Ubuntu Hardy’s verison is 1.6):

gcc -o jpeg2bw jpeg2bw.c -ljpeg -lguile -lm

Usage is (info on the PNM image format):

./jpeg2bw color_image.jpg > bw_image.pnm

The results

I then scaled each image down for the web, added a bit of local contrast and unsharp mask (same amount for each image, of course). And here are the results, in no particular order:

A.

B.

C.

D.

Which one do you like best, and why? (I’ll put the correspondance method – result in a later post)

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